diff --git a/stitch_project/api/Playground.ipynb b/stitch_project/api/Playground.ipynb
index 39e40e43d000ede380075aff982203fc3aa62eb5..c994a6775550472ff176609fa809e52d3b3f9780 100644
--- a/stitch_project/api/Playground.ipynb
+++ b/stitch_project/api/Playground.ipynb
@@ -17,7 +17,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "9e1f5cc3",
+   "id": "109d349c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -29,7 +29,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "689c3a90",
+   "id": "f94d622b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -57,49 +57,51 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 26,
    "id": "cdf25108",
    "metadata": {},
    "outputs": [],
    "source": [
-    "frequenciesHz = np.linspace(630., 680., 50)\n",
+    "frequenciesHz = np.linspace(630., 680., 100)\n",
     "#rampsHzSq = np.full_like(frequenciesHz, 100.)\n",
     "Q=70.\n",
     "rampsHzSq=np.diff(frequenciesHz)/(Q/frequenciesHz[:-1])\n",
     "ringupPeriods = np.full_like(frequenciesHz, 70.)\n",
     "#measurePeriods = np.full_like(frequenciesHz, 200)\n",
-    "measurePeriods = np.full_like(frequenciesHz, 70)"
+    "measurePeriods = np.full_like(frequenciesHz, 3000)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 27,
    "id": "c13777a7",
    "metadata": {},
    "outputs": [],
    "source": [
     "freqsDphi = [frequencyHzToDphi(x) for x in frequenciesHz]\n",
     "rampsDdphi = [rampHzSqToDdphi(x) for x in rampsHzSq]\n",
+    "rampsDdphi.append(rampsDdphi[-1])\n",
     "nSweeps = []\n",
     "for i in range(1,len(freqsDphi)):\n",
     "    nSweeps.append(DeltaDphiAndDdphiToNsweep(freqsDphi[i]-freqsDphi[i-1], rampsDdphi[i-1]))\n",
+    "nSweeps.append(nSweeps[-1])\n",
     "nRingup = [numPeriodsToNringup(ringupPeriods[i], frequenciesHz[i]) for i in range(len(frequenciesHz))]\n",
     "nMeas = [numPeriodsToNmeas(measurePeriods[i], frequenciesHz[i]) for i in range(len(frequenciesHz))]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "id": "4713e663",
+   "execution_count": 28,
+   "id": "abbf7709",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "16.31279612"
+       "240.19492249"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -110,7 +112,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 29,
+   "id": "774f4c1c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "50"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(nSweeps)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
    "id": "32a815cc",
    "metadata": {},
    "outputs": [],
@@ -125,7 +148,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 31,
    "id": "54a896c3",
    "metadata": {},
    "outputs": [],
@@ -135,7 +158,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 32,
    "id": "741dcc42",
    "metadata": {},
    "outputs": [
@@ -153,8 +176,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "id": "d4121d94",
+   "execution_count": 33,
+   "id": "62fdbd06",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -163,8 +186,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "id": "2fa44179",
+   "execution_count": 34,
+   "id": "99368cb7",
    "metadata": {},
    "outputs": [
     {
@@ -1135,7 +1158,7 @@
     {
      "data": {
       "text/html": [
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\" 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+       "<img 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\" width=\"800\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -1150,7 +1173,7 @@
        "Text(0, 0.5, 'Response Phase [rad]')"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1173,16 +1196,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "677d9aa4",
+   "execution_count": 35,
+   "id": "17f6f196",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[5175951 5167581 5159239 5150923 5142634 5134371 5126135 5117925 5109742\n",
+      " 5101585 5093454 5085348 5077268 5069214 5061186 5053183 5045206 5037252\n",
+      " 5029325 5021422 5013544 5005691 4997862 4990058 4982278 4974522 4966791\n",
+      " 4959083 4951400 4943740 4936103 4928490 4920902 4913335 4905793 4898273\n",
+      " 4890777 4883302 4875851 4868424 4861018 4853635 4846274 4838936 4831620\n",
+      " 4824326 4817053 4809803 4802575 4795368]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(nums)"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "id": "e872ceb2",
+   "execution_count": 55,
+   "id": "4bcde53f",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1192,7 +1230,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f6121be9",
+   "id": "9b1f7d17",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1200,7 +1238,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a864025b",
+   "id": "68cb0f19",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1208,7 +1246,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c0b1612d",
+   "id": "33783fb4",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1216,7 +1254,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a0c18c06",
+   "id": "078a5386",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1224,7 +1262,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5b10377e",
+   "id": "b54b8da0",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1232,7 +1270,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "39bc02c3",
+   "id": "56bee8e2",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1240,7 +1278,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7f94af5d",
+   "id": "b54e447a",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1248,7 +1286,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d21a64cb",
+   "id": "b176a759",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1256,7 +1294,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4215a9d9",
+   "id": "05e93761",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1264,7 +1302,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6cd6ac76",
+   "id": "30701990",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1272,7 +1310,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "558bb3f1",
+   "id": "8d53e7f2",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1280,7 +1318,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a231d7bb",
+   "id": "4566d464",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1288,7 +1326,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2ead7c49",
+   "id": "b740809c",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1296,7 +1334,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "288246f1",
+   "id": "696eceaf",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1304,7 +1342,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e791256f",
+   "id": "078f2348",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1312,7 +1350,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "39076be9",
+   "id": "8d433590",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1320,7 +1358,7 @@
   {
    "cell_type": "code",
    "execution_count": 77,
-   "id": "71ef92de",
+   "id": "6882f11b",
    "metadata": {},
    "outputs": [
     {
@@ -1342,7 +1380,7 @@
   {
    "cell_type": "code",
    "execution_count": 362,
-   "id": "ed4126ce",
+   "id": "2a20c47a",
    "metadata": {},
    "outputs": [
     {
@@ -1363,7 +1401,7 @@
   {
    "cell_type": "code",
    "execution_count": 189,
-   "id": "0847334d",
+   "id": "59bbc97f",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1375,7 +1413,7 @@
   {
    "cell_type": "code",
    "execution_count": 190,
-   "id": "e99d3048",
+   "id": "5993f642",
    "metadata": {},
    "outputs": [
     {
@@ -2374,7 +2412,7 @@
   {
    "cell_type": "code",
    "execution_count": 439,
-   "id": "d6695880",
+   "id": "c198a4a3",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2406,7 +2444,7 @@
   {
    "cell_type": "code",
    "execution_count": 440,
-   "id": "f494e5bb",
+   "id": "465ad2cd",
    "metadata": {},
    "outputs": [
     {
@@ -3416,7 +3454,7 @@
   {
    "cell_type": "code",
    "execution_count": 377,
-   "id": "c69fa3a8",
+   "id": "4cbe9a0b",
    "metadata": {},
    "outputs": [
     {
@@ -4417,7 +4455,7 @@
   {
    "cell_type": "code",
    "execution_count": 100,
-   "id": "d0f0a9cd",
+   "id": "9a23531d",
    "metadata": {
     "scrolled": true
    },
@@ -4537,7 +4575,7 @@
   {
    "cell_type": "code",
    "execution_count": 221,
-   "id": "1cb2888a",
+   "id": "c59f100a",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4547,7 +4585,7 @@
   {
    "cell_type": "code",
    "execution_count": 271,
-   "id": "1b7cb2aa",
+   "id": "d444f80d",
    "metadata": {},
    "outputs": [
     {
@@ -5098,7 +5136,7 @@
   {
    "cell_type": "code",
    "execution_count": 287,
-   "id": "52880e59",
+   "id": "2b571658",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5118,7 +5156,7 @@
   {
    "cell_type": "code",
    "execution_count": 288,
-   "id": "cf752f9c",
+   "id": "f88fa93f",
    "metadata": {
     "scrolled": false
    },
@@ -6125,7 +6163,7 @@
   {
    "cell_type": "code",
    "execution_count": 298,
-   "id": "0e47fe88",
+   "id": "e1a520a5",
    "metadata": {},
    "outputs": [
     {
@@ -6146,7 +6184,7 @@
   {
    "cell_type": "code",
    "execution_count": 295,
-   "id": "b4d976bc",
+   "id": "3f9bafd6",
    "metadata": {},
    "outputs": [
     {
@@ -6167,7 +6205,7 @@
   {
    "cell_type": "code",
    "execution_count": 361,
-   "id": "6d88e0c0",
+   "id": "7727da25",
    "metadata": {},
    "outputs": [
     {
@@ -6185,7 +6223,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7cd5295e",
+   "id": "a6aae057",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -6193,7 +6231,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "c645fc42",
+   "id": "e74bf320",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -6203,7 +6241,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "5a560000",
+   "id": "6ce5d639",
    "metadata": {},
    "outputs": [
     {
@@ -7213,7 +7251,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d5b527d4",
+   "id": "533ea610",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -7221,7 +7259,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d4496044",
+   "id": "b114de8b",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -7229,7 +7267,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "153c5e5e",
+   "id": "cef4677b",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -7237,7 +7275,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e3444915",
+   "id": "a419a310",
    "metadata": {},
    "outputs": [],
    "source": []
diff --git a/stitch_project/stitch/DistanceUnwrapper.vhd b/stitch_project/stitch/DistanceUnwrapper.vhd
new file mode 100644
index 0000000000000000000000000000000000000000..df55a193545a21a47559a5da755a3627cd3ab018
--- /dev/null
+++ b/stitch_project/stitch/DistanceUnwrapper.vhd
@@ -0,0 +1,161 @@
+----------------------------------------------------------------------------------
+-- Company: ETH Zurich
+-- Engineer: Pascal Engeler <engeler.pascal@gmail.com>
+-- 
+-- Create Date:    14:32:01 09/06/2024 
+-- Design Name: 
+-- Module Name:    DistanceUnwrapper - Behavioral 
+-- Project Name: 
+-- Target Devices: 
+-- Tool versions: 
+-- Description: 
+--
+-- Dependencies: 
+--
+-- Revision: 
+-- Revision 0.01 - File Created
+-- Additional Comments: 
+--
+----------------------------------------------------------------------------------
+library IEEE;
+use IEEE.STD_LOGIC_1164.ALL;
+use IEEE.STD_LOGIC_UNSIGNED.ALL;
+use IEEE.NUMERIC_STD.ALL;
+
+entity DistanceUnwrapper is
+    Port (  clk100			: in STD_LOGIC;
+			en 				: in  STD_LOGIC;
+			dr				: in STD_LOGIC;
+		    distance_in	 	: in  STD_LOGIC_VECTOR(20 downto 0);
+            distance_out    : out STD_LOGIC_VECTOR(24 downto 0);
+			dr_out			: out STD_LOGIC);
+end DistanceUnwrapper;
+
+architecture Behavioral of DistanceUnwrapper is
+
+type STATE_T is (IDLE_S, STATE1, STATE2, STATE3);
+
+signal current_state : STATE_T := IDLE_S;
+
+signal currentDistance : STD_LOGIC_VECTOR(24 downto 0) := (others => '0');
+signal prevDistance : STD_LOGIC_VECTOR(24 downto 0) := (others => '0');
+signal latchedDistance : STD_LOGIC_VECTOR(24 downto 0) := (others => '0');
+signal distanceInWide : STD_LOGIC_VECTOR(24 downto 0) := (others => '0');
+signal calcDelta : STD_LOGIC_VECTOR(24 downto 0) := (others => '0');
+
+signal maxDelta : STD_LOGIC_VECTOR(24 downto 0) := "0000100000000000000000000";
+signal corrDelta : STD_LOGIC_VECTOR(24 downto 0) := "0001000000000000000000000";
+signal corrDeltaN : STD_LOGIC_VECTOR(24 downto 0) := "1111000000000000000000000";
+signal currentOffset : STD_LOGIC_VECTOR(24 downto 0) := (others => '0');
+
+signal newIsLarger : STD_LOGIC := '0';
+
+signal dr_prev : STD_LOGIC := '0';
+
+begin
+
+distanceInWide(20 downto 0) <= distance_in;
+distanceInWide(24 downto 21) <= (others => '0');
+
+distance_out <= currentDistance;
+
+
+dr_update: process(clk100)
+begin
+	if rising_edge(clk100) then
+		dr_prev <= dr;
+	end if;
+end process;
+
+
+
+proc: process(clk100)
+begin
+	if rising_edge(clk100) then
+		if en = '1' then
+			case current_state is
+			when IDLE_S =>
+				if dr = '1' and dr_prev = '0' then
+					current_state <= STATE1;
+					latchedDistance <= distanceInWide;
+					--calculate relevant delta distance here
+					if prevDistance > distanceInWide then
+						newIsLarger <= '0';
+						calcDelta <= prevDistance - distanceInWide;
+					else 
+						newIsLarger <= '1';
+						calcDelta <= distanceInWide - prevDistance;
+					end if;
+				else
+					current_state <= IDLE_S;
+					latchedDistance <= latchedDistance;
+					newIsLarger <= newIsLarger;
+					calcDelta <= calcDelta;
+				end if;
+				currentOffset <= currentOffset;
+				currentDistance <= currentDistance;
+				dr_out <= '0';
+				prevDistance <= prevDistance;
+
+			when STATE1 =>
+				current_state <= STATE2;
+				--calculate change to offset here 
+				if calcDelta > maxDelta then
+					--we have wrapped around 
+					if newIsLarger = '1' then
+						--went negative
+						currentOffset <= currentOffset + corrDeltaN;
+					else 
+						--went more positive
+						currentOffset <= currentOffset + corrDelta;
+					end if;
+				else 
+					currentOffset <= currentOffset;
+				end if;
+				latchedDistance <= latchedDistance;
+				newIsLarger <= newIsLarger;
+				calcDelta <= calcDelta;
+				currentDistance <= currentDistance;
+				dr_out <= '0';
+				prevDistance <= prevDistance;
+					
+			when STATE2 => 
+			--calculate output distance, set next prevDistance here
+				current_state <= STATE3;
+				currentDistance <= currentOffset + latchedDistance;
+				latchedDistance <= latchedDistance;
+				newIsLarger <= newIsLarger;
+				calcDelta <= calcDelta;
+				currentOffset <= currentOffset;
+				dr_out <= '0';
+				prevDistance <= latchedDistance;
+
+			when STATE3 =>
+			--set output ready here	
+				current_state <= IDLE_S;
+				dr_out <= '1';
+				latchedDistance <= latchedDistance;
+				newIsLarger <= newIsLarger;
+				calcDelta <= calcDelta;
+				currentOffset <= currentOffset;
+				currentDistance <= currentDistance;
+				prevDistance <= prevDistance;
+			end case;
+
+		else 
+			currentDistance <= (others => '0');
+			prevDistance <= (others => '0');
+			current_state <= IDLE_S;
+			latchedDistance <= (others => '0');
+			newIsLarger <= '0';
+			calcDelta <= (others => '0');
+			currentOffset <= (others => '0');
+			dr_out <= '0';
+		end if;
+
+	end if;
+		
+end process;
+
+end Behavioral;
+
diff --git a/stitch_project/stitch/LockInAccumulator.vhd b/stitch_project/stitch/LockInAccumulator.vhd
index c92f8f62bf60c2797857e35d3f621170eccd9985..a50619d378cdfda554e689f50192549a17acfdda 100644
--- a/stitch_project/stitch/LockInAccumulator.vhd
+++ b/stitch_project/stitch/LockInAccumulator.vhd
@@ -27,7 +27,7 @@ entity LockInAccumulator is
     Port ( CLK100 : in  STD_LOGIC;
            sin : in STD_LOGIC_VECTOR(20 downto 0);
            cos : in STD_LOGIC_VECTOR(20 downto 0);
-           data : in STD_LOGIC_VECTOR(20 downto 0);
+           data : in STD_LOGIC_VECTOR(24 downto 0);
            trig : in STD_LOGIC;
            clear : in STD_LOGIC;
            enable : in STD_LOGIC;
@@ -45,9 +45,9 @@ signal current_state: STATE_T := STATE_IDLE;
 signal clear_old: STD_LOGIC := '0';
 signal trig_old: STD_LOGIC := '0';
 
-signal sinInternal : STD_LOGIC_VECTOR(20 downto 0);
-signal cosInternal : STD_LOGIC_VECTOR(20 downto 0);
-signal dataInternal : STD_LOGIC_VECTOR(20 downto 0);
+signal sinInternal : STD_LOGIC_VECTOR(24 downto 0) := (others => '0');
+signal cosInternal : STD_LOGIC_VECTOR(24 downto 0) := (others => '0');
+signal dataInternal : STD_LOGIC_VECTOR(24 downto 0) := (others => '0');
 signal trigInternal : STD_LOGIC := '0';
 signal enableInternal : STD_LOGIC := '1';
 signal clearInternal : STD_LOGIC := '0';
@@ -55,9 +55,9 @@ signal bypassInternal : STD_LOGIC := '0';
 signal n_samples_int : STD_LOGIC_VECTOR(31 downto 0) := (others => '0');
 signal idle_int: STD_LOGIC := '1';
 
-signal sinApplied : STD_LOGIC_VECTOR(20 downto 0) := (others => '0');
-signal cosApplied : STD_LOGIC_VECTOR(20 downto 0) := (others => '0');
-signal dataApplied : STD_LOGIC_VECTOR(20 downto 0) := (others => '0');
+signal sinApplied : STD_LOGIC_VECTOR(24 downto 0) := (others => '0');
+signal cosApplied : STD_LOGIC_VECTOR(24 downto 0) := (others => '0');
+signal dataApplied : STD_LOGIC_VECTOR(24 downto 0) := (others => '0');
 
 signal dataAccumSin : STD_LOGIC_VECTOR(69 downto 0);
 signal dataAccumCos : STD_LOGIC_VECTOR(69 downto 0);
@@ -69,8 +69,8 @@ PORT (
     ce : IN STD_LOGIC;
     sclr : IN STD_LOGIC;
     bypass : IN STD_LOGIC;
-    a : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
-    b : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
+    a : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
+    b : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
     s : OUT STD_LOGIC_VECTOR(69 DOWNTO 0)
   );
 END COMPONENT;
@@ -80,8 +80,8 @@ PORT (
     ce : IN STD_LOGIC;
     sclr : IN STD_LOGIC;
     bypass : IN STD_LOGIC;
-    a : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
-    b : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
+    a : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
+    b : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
     s : OUT STD_LOGIC_VECTOR(69 DOWNTO 0)
   );
 END COMPONENT;
@@ -120,8 +120,17 @@ begin
     if rising_edge(CLK100) then
         case current_state is
             when STATE_IDLE =>
-                sinInternal <= sin;
-                cosInternal <= cos;
+                --latch SIGNED sin by sign extending
+                sinInternal(20 downto 0) <= sin;
+                sinInternal(24) <= sin(20);
+                sinInternal(23) <= sin(20);
+                sinInternal(22) <= sin(20);
+                sinInternal(21) <= sin(20);
+                cosInternal(20 downto 0) <= cos;
+                cosInternal(24) <= cos(20);
+                cosInternal(23) <= cos(20);
+                cosInternal(22) <= cos(20);
+                cosInternal(21) <= cos(20);
                 dataInternal <= data;
                 sinApplied <= (others => '0');
                 cosApplied <= (others => '0');
diff --git a/stitch_project/stitch/Stitch.bin b/stitch_project/stitch/Stitch.bin
index 4d41ba5abb3316119ba9fa2497fb37162d8a16ae..8d4c004b70b47e31ac1f6115a9baf57aa7643d60 100644
Binary files a/stitch_project/stitch/Stitch.bin and b/stitch_project/stitch/Stitch.bin differ
diff --git a/stitch_project/stitch/Stitch.vhd b/stitch_project/stitch/Stitch.vhd
index 75e81e2ae7110d1e07f179fab31768b4a60967d3..ca2cf883b759d8b36bf5d8b8af82e0ed5e675e88 100644
--- a/stitch_project/stitch/Stitch.vhd
+++ b/stitch_project/stitch/Stitch.vhd
@@ -107,6 +107,9 @@ signal iLockInAccumulator_dataSin : STD_LOGIC_VECTOR(63 downto 0);
 signal iLockInAccumulator_n_samples : STD_LOGIC_VECTOR(31 downto 0);
 signal iLockInAccumulator_idle : STD_LOGIC;
 
+signal iDistanceUnwrapper_distance_out : STD_LOGIC_VECTOR(24 downto 0);
+signal iDistanceUnwrapper_dr_out : STD_LOGIC;
+
 signal iCordic_x_out : STD_LOGIC_VECTOR(20 DOWNTO 0);
 signal iCordic_y_out : STD_LOGIC_VECTOR(20 DOWNTO 0);
 signal iCordic_rdy : STD_LOGIC;
@@ -193,12 +196,23 @@ Port (
 );
 END COMPONENT;
 
+COMPONENT DistanceUnwrapper
+Port (
+    clk100 : in STD_LOGIC;
+    en : in STD_LOGIC;
+    dr : in STD_LOGIC;
+    distance_in : in STD_LOGIC_VECTOR(20 downto 0);
+    distance_out : out STD_LOGIC_VECTOR(24 downto 0);
+    dr_out : out STD_LOGIC
+);
+END COMPONENT;
+
 COMPONENT LockInAccumulator
 Port ( 
     CLK100 : in  STD_LOGIC;
     sin : in STD_LOGIC_VECTOR(20 downto 0);
     cos : in STD_LOGIC_VECTOR(20 downto 0);
-    data : in STD_LOGIC_VECTOR(20 downto 0);
+    data : in STD_LOGIC_VECTOR(24 downto 0);
     trig : in STD_LOGIC;
     clear : in STD_LOGIC;
     enable : in STD_LOGIC;
@@ -318,6 +332,10 @@ PORT (
 );
 END COMPONENT;
 
+--signals to detect unwrapping
+signal or_24_23 : STD_LOGIC;
+signal or_22_21 : STD_LOGIC;
+
 
 begin
 -- route signals here
@@ -412,9 +430,13 @@ STX <= iSerialTransmitter_TX;
 
 DDS_OUT <= iSweeper_phi(28);
 
-LEDS(0) <= '1';
+--LEDS(0) <= '1';
+LEDS(0) <= iDistanceUnwrapper_dr_out;
 LEDS(1) <= NOT iSweeper_idle;
-LEDS(2) <= NOT iReadbackControl_idle;
+--LEDS(2) <= NOT iReadbackControl_idle;
+or_24_23 <= iDistanceUnwrapper_distance_out(24) OR iDistanceUnwrapper_distance_out(23);
+or_22_21 <= iDistanceUnwrapper_distance_out(22) OR iDistanceUnwrapper_distance_out(21);
+LEDS(2) <= or_24_23 OR or_22_21;
 
 phi_clean(31 downto 1) <= iSweeper_phi(30 downto 0);
 phi_clean(0) <= '0';
@@ -493,8 +515,8 @@ iLockInAccumulator : LockInAccumulator port map(
 	CLK100 => Stitch_CLK100,  -- in  STD_LOGIC
 	sin => iCordic_y_out,  -- in STD_LOGIC_VECTOR(20 downto 0)
 	cos => iCordic_x_out,  -- in STD_LOGIC_VECTOR(20 downto 0)
-	data => iLaserReceiver_DISTANCE,  -- in STD_LOGIC_VECTOR(20 downto 0)
-	trig => iLaserReceiver_DATA_READY,  -- in STD_LOGIC
+	data => iDistanceUnwrapper_distance_out,  -- in STD_LOGIC_VECTOR(20 downto 0)
+	trig => iDistanceUnwrapper_dr_out,  -- in STD_LOGIC
 	clear => iSweeper_lockin_clear,  -- in STD_LOGIC
 	enable => iSweeper_lockin_en,  -- in STD_LOGIC
 	dataCos => iLockInAccumulator_dataCos,  -- out STD_LOGIC_VECTOR(63 downto 0)
@@ -503,6 +525,15 @@ iLockInAccumulator : LockInAccumulator port map(
 	idle => iLockInAccumulator_idle  -- out STD_LOGIC
 );
 
+iDistanceUnwrapper : DistanceUnwrapper port map(
+    clk100 => Stitch_CLK100,
+    en => iSweeper_lockin_en,
+    dr => iLaserReceiver_DATA_READY,
+    distance_in => iLaserReceiver_DISTANCE,
+    distance_out => iDistanceUnwrapper_distance_out,
+    dr_out => iDistanceUnwrapper_dr_out
+);
+
 --TODO: The clocking and data input and stuff may need some optimizations. Refer to the manual in ISE, esp. pertaining parallel vs word serial
 iCordic : cordic port map(
 	phase_in => phi_clean,  -- IN STD_LOGIC_VECTOR(31 DOWNTO 0)
diff --git a/stitch_project/stitch/_xmsgs/pn_parser.xmsgs b/stitch_project/stitch/_xmsgs/pn_parser.xmsgs
index 16de26385b98a5cbd151f34bd688ea6645e78d33..4cdaa9767e70148984c56ee97d0583b3eae6393f 100644
--- a/stitch_project/stitch/_xmsgs/pn_parser.xmsgs
+++ b/stitch_project/stitch/_xmsgs/pn_parser.xmsgs
@@ -8,32 +8,8 @@
 <!-- Copyright (c) 1995-2013 Xilinx, Inc.  All rights reserved.    -->
 
 <messages>
-<msg type="info" file="ProjectMgmt" num="1061" ><arg fmt="%s" index="1">Parsing VHDL file &quot;/home/ise/iseprojects/stitch/stitch_project/stitch/Beeper.vhd&quot; into library work</arg>
-</msg>
-
-<msg type="info" file="ProjectMgmt" num="1061" ><arg fmt="%s" index="1">Parsing VHDL file &quot;/home/ise/iseprojects/stitch/stitch_project/stitch/CommandDecoder.vhd&quot; into library work</arg>
-</msg>
-
-<msg type="info" file="ProjectMgmt" num="1061" ><arg fmt="%s" index="1">Parsing VHDL file &quot;/home/ise/iseprojects/stitch/stitch_project/stitch/LaserReceiver.vhd&quot; into library work</arg>
-</msg>
-
-<msg type="info" file="ProjectMgmt" num="1061" ><arg fmt="%s" index="1">Parsing VHDL file &quot;/home/ise/iseprojects/stitch/stitch_project/stitch/LockInAccumulator.vhd&quot; into library work</arg>
-</msg>
-
-<msg type="info" file="ProjectMgmt" num="1061" ><arg fmt="%s" index="1">Parsing VHDL file &quot;/home/ise/iseprojects/stitch/stitch_project/stitch/ReadbackControl.vhd&quot; into library work</arg>
-</msg>
-
-<msg type="info" file="ProjectMgmt" num="1061" ><arg fmt="%s" index="1">Parsing VHDL file &quot;/home/ise/iseprojects/stitch/stitch_project/stitch/SerialReceiver.vhd&quot; into library work</arg>
-</msg>
-
-<msg type="info" file="ProjectMgmt" num="1061" ><arg fmt="%s" index="1">Parsing VHDL file &quot;/home/ise/iseprojects/stitch/stitch_project/stitch/SerialTransmitter.vhd&quot; into library work</arg>
-</msg>
-
 <msg type="info" file="ProjectMgmt" num="1061" ><arg fmt="%s" index="1">Parsing VHDL file &quot;/home/ise/iseprojects/stitch/stitch_project/stitch/Stitch.vhd&quot; into library work</arg>
 </msg>
 
-<msg type="info" file="ProjectMgmt" num="1061" ><arg fmt="%s" index="1">Parsing VHDL file &quot;/home/ise/iseprojects/stitch/stitch_project/stitch/Sweeper.vhd&quot; into library work</arg>
-</msg>
-
 </messages>
 
diff --git a/stitch_project/stitch/ipcore_dir/Mem32b1024.gise b/stitch_project/stitch/ipcore_dir/Mem32b1024.gise
index 75eab9585225cccac533b9dee87aa77a05e031d7..830ccb29bfef980f8a22e3f7dbab1899d5ce2239 100644
--- a/stitch_project/stitch/ipcore_dir/Mem32b1024.gise
+++ b/stitch_project/stitch/ipcore_dir/Mem32b1024.gise
@@ -32,19 +32,19 @@
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="3185129189393661258" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="3185129189393661258" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="7316991560476725013" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="7316991560476725013" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="-4997764571106617334" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="-4997764571106617334" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
diff --git a/stitch_project/stitch/ipcore_dir/MemNsamp.gise b/stitch_project/stitch/ipcore_dir/MemNsamp.gise
index 2bae611f6e38d469d52760f9f11f5934ae428d15..20bca32e67b1d269e300cf29da9104cb89793513 100644
--- a/stitch_project/stitch/ipcore_dir/MemNsamp.gise
+++ b/stitch_project/stitch/ipcore_dir/MemNsamp.gise
@@ -32,19 +32,19 @@
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="-6820686459059339956" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="-6820686459059339956" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="-7915863299109585449" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="-7915863299109585449" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="5925673752377620492" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="5925673752377620492" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
diff --git a/stitch_project/stitch/ipcore_dir/MemSinCos.gise b/stitch_project/stitch/ipcore_dir/MemSinCos.gise
index 3d0d8861a4dbe785de5d8d8b81ca82600a182c62..fa0f8d8fc0dd776e65d89c0c95750b8c4bf5f0c6 100644
--- a/stitch_project/stitch/ipcore_dir/MemSinCos.gise
+++ b/stitch_project/stitch/ipcore_dir/MemSinCos.gise
@@ -32,19 +32,19 @@
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="-2788987222142637780" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="-2788987222142637780" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="4978056458918207415" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="4978056458918207415" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="6045739603124474860" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="6045739603124474860" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
diff --git a/stitch_project/stitch/ipcore_dir/_xmsgs/cg.xmsgs b/stitch_project/stitch/ipcore_dir/_xmsgs/cg.xmsgs
index a9041a7ff61d88a82dff7c77450ed472c9619d10..3ba78be9cabac17eaf8ad2002f9629139a0e710c 100644
--- a/stitch_project/stitch/ipcore_dir/_xmsgs/cg.xmsgs
+++ b/stitch_project/stitch/ipcore_dir/_xmsgs/cg.xmsgs
@@ -8,5 +8,20 @@
 <msg type="info" file="sim" num="172" delta="old" >Generating IP...
 </msg>
 
+<msg type="warning" file="sim" num="0" delta="new" ><arg fmt="%s" index="1">A core named &apos;multiaddCos&apos; already exists in the project. Output products for this core may be overwritten.</arg>
+</msg>
+
+<msg type="warning" file="sim" num="0" delta="new" ><arg fmt="%s" index="1">A core named &apos;multiaddCos&apos; already exists in the project. Output products for this core may be overwritten.</arg>
+</msg>
+
+<msg type="info" file="sim" num="0" delta="new" ><arg fmt="%s" index="1">Pre-processing HDL files for &apos;multiaddCos&apos;...</arg>
+</msg>
+
+<msg type="info" file="sim" num="949" delta="old" >Finished generation of ASY schematic symbol.
+</msg>
+
+<msg type="info" file="sim" num="948" delta="old" >Finished FLIST file generation.
+</msg>
+
 </messages>
 
diff --git a/stitch_project/stitch/ipcore_dir/cordic.gise b/stitch_project/stitch/ipcore_dir/cordic.gise
index 21a8d1d8bb1ebdb9ed1b5d7fe0c6c287046ccc60..bed77bfa79f4bf499f0e731f401a51467a5bb227 100644
--- a/stitch_project/stitch/ipcore_dir/cordic.gise
+++ b/stitch_project/stitch/ipcore_dir/cordic.gise
@@ -32,19 +32,19 @@
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="-8782926585333300168" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="-8782926585333300168" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="7818039811878659395" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="7818039811878659395" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="3776669437272252152" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="3776669437272252152" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
diff --git a/stitch_project/stitch/ipcore_dir/coregen.log b/stitch_project/stitch/ipcore_dir/coregen.log
index 84facf168f28a1497bb03851fb6169469f4f988e..d6cdda59325d0c1c6f966838f0b3317a3c7fcad8 100644
--- a/stitch_project/stitch/ipcore_dir/coregen.log
+++ b/stitch_project/stitch/ipcore_dir/coregen.log
@@ -1,5 +1,69 @@
 INFO:sim:172 - Generating IP...
 Applying current project options...
 Finished applying current project options.
-Cancelled executing Tcl generator.
-Wrote CGP file for project 'cordic'.
+WARNING:sim - A core named 'multiaddCos' already exists in the project. Output
+   products for this core may be overwritten.
+Resolving generics for 'multiaddCos'...
+WARNING:sim - A core named 'multiaddCos' already exists in the project. Output
+   products for this core may be overwritten.
+Applying external generics to 'multiaddCos'...
+Delivering associated files for 'multiaddCos'...
+Generating implementation netlist for 'multiaddCos'...
+INFO:sim - Pre-processing HDL files for 'multiaddCos'...
+Running synthesis for 'multiaddCos'
+Running ngcbuild...
+Writing VHO instantiation template for 'multiaddCos'...
+Writing VHDL behavioral simulation model for 'multiaddCos'...
+Delivered 3 files into directory
+/home/ise/iseprojects/stitch/stitch_project/stitch/ipcore_dir/tmp/_cg/multiaddCo
+s
+Generating ASY schematic symbol...
+INFO:sim:949 - Finished generation of ASY schematic symbol.
+Generating SYM schematic symbol for 'multiaddCos'...
+Generating metadata file...
+Generating ISE project...
+XCO file found: multiaddCos.xco
+XMDF file found: multiaddCos_xmdf.tcl
+Adding
+/home/ise/iseprojects/stitch/stitch_project/stitch/ipcore_dir/tmp/_cg/core_resou
+rces.txt -view all -origin_type imported
+Adding
+/home/ise/iseprojects/stitch/stitch_project/stitch/ipcore_dir/tmp/_cg/gui_latenc
+y.txt -view all -origin_type imported
+Adding
+/home/ise/iseprojects/stitch/stitch_project/stitch/ipcore_dir/tmp/_cg/multiaddCo
+s.asy -view all -origin_type imported
+Adding
+/home/ise/iseprojects/stitch/stitch_project/stitch/ipcore_dir/tmp/_cg/multiaddCo
+s.ngc -view all -origin_type created
+Checking file
+"/home/ise/iseprojects/stitch/stitch_project/stitch/ipcore_dir/tmp/_cg/multiaddC
+os.ngc" for project device match ...
+File
+"/home/ise/iseprojects/stitch/stitch_project/stitch/ipcore_dir/tmp/_cg/multiaddC
+os.ngc" device information matches project device.
+Adding
+/home/ise/iseprojects/stitch/stitch_project/stitch/ipcore_dir/tmp/_cg/multiaddCo
+s.sym -view all -origin_type imported
+Adding
+/home/ise/iseprojects/stitch/stitch_project/stitch/ipcore_dir/tmp/_cg/multiaddCo
+s.vhd -view all -origin_type created
+INFO:HDLCompiler:1061 - Parsing VHDL file
+   "/home/ise/iseprojects/stitch/stitch_project/stitch/ipcore_dir/tmp/_cg/multia
+   ddCos.vhd" into library work
+INFO:ProjectMgmt - Parsing design hierarchy completed successfully.
+Adding
+/home/ise/iseprojects/stitch/stitch_project/stitch/ipcore_dir/tmp/_cg/multiaddCo
+s.vho -view all -origin_type imported
+INFO:TclTasksC:2116 - The automatic calculation of top has been turned-off.
+   Please set the new top explicitly by running the "project set top" command.
+   To re-calculate the new top automatically, set the "Auto Implementation Top"
+   property to true.
+Top level has been set to "/multiaddCos"
+Generating README file...
+Generating FLIST file...
+INFO:sim:948 - Finished FLIST file generation.
+Launching README viewer...
+Moving files to output directory...
+Finished moving files to output directory
+Wrote CGP file for project 'multiaddCos'.
diff --git a/stitch_project/stitch/ipcore_dir/multiaddCos.asy b/stitch_project/stitch/ipcore_dir/multiaddCos.asy
index 45290d76a353a51ba271a0bfa50e2274414cb86f..41c94d729db9e3783e245ab772297b439d8999eb 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddCos.asy
+++ b/stitch_project/stitch/ipcore_dir/multiaddCos.asy
@@ -4,11 +4,11 @@ TEXT 32 32 LEFT 4 multiaddCos
 RECTANGLE Normal 32 32 256 320
 LINE Wide 0 80 32 80
 PIN 0 80 LEFT 36
-PINATTR PinName a[20:0]
+PINATTR PinName a[24:0]
 PINATTR Polarity IN
 LINE Wide 0 112 32 112
 PIN 0 112 LEFT 36
-PINATTR PinName b[20:0]
+PINATTR PinName b[24:0]
 PINATTR Polarity IN
 LINE Normal 0 144 32 144
 PIN 0 144 LEFT 36
diff --git a/stitch_project/stitch/ipcore_dir/multiaddCos.gise b/stitch_project/stitch/ipcore_dir/multiaddCos.gise
index f7f2ac2dccf1f5d0bf6caf46d93d1bde7c484e09..292844d3ce5310a9d8d325683b51777ec3dbbedd 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddCos.gise
+++ b/stitch_project/stitch/ipcore_dir/multiaddCos.gise
@@ -34,19 +34,19 @@
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="-6854975743064405440" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="-6854975743064405440" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="8175489371127869360" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="8175489371127869360" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="4442281788066732546" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="4442281788066732546" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
diff --git a/stitch_project/stitch/ipcore_dir/multiaddCos.ngc b/stitch_project/stitch/ipcore_dir/multiaddCos.ngc
index b6adffc63355fb59c99f9183a46a19e25e7c67ec..e679e4393a4ca26904bb39044165678edbdd6499 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddCos.ngc
+++ b/stitch_project/stitch/ipcore_dir/multiaddCos.ngc
@@ -1,3 +1,3 @@
 XILINX-XDB 0.1 STUB 0.1 ASCII
 XILINX-XDM V1.6e
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diff --git a/stitch_project/stitch/ipcore_dir/multiaddCos.sym b/stitch_project/stitch/ipcore_dir/multiaddCos.sym
index 6e599a4937fc0ada157003cd5836a8db823071ae..f5da469e94a67dddd817fe5db7b1049d87f812cc 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddCos.sym
+++ b/stitch_project/stitch/ipcore_dir/multiaddCos.sym
@@ -1,9 +1,9 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <symbol version="7" name="multiaddCos">
     <symboltype>BLOCK</symboltype>
-    <timestamp>2024-8-29T8:48:0</timestamp>
-    <pin polarity="Input" x="0" y="80" name="a[20:0]" />
-    <pin polarity="Input" x="0" y="112" name="b[20:0]" />
+    <timestamp>2024-9-10T14:36:21</timestamp>
+    <pin polarity="Input" x="0" y="80" name="a[24:0]" />
+    <pin polarity="Input" x="0" y="112" name="b[24:0]" />
     <pin polarity="Input" x="0" y="144" name="clk" />
     <pin polarity="Input" x="0" y="208" name="ce" />
     <pin polarity="Input" x="0" y="240" name="bypass" />
@@ -13,9 +13,9 @@
         <text style="fontsize:40;fontname:Arial" x="32" y="32">multiaddCos</text>
         <rect width="224" x="32" y="32" height="288" />
         <line x2="32" y1="80" y2="80" style="linewidth:W" x1="0" />
-        <attrtext style="fontsize:24;fontname:Arial" attrname="PinName" x="36" y="80" type="pin a[20:0]" />
+        <attrtext style="fontsize:24;fontname:Arial" attrname="PinName" x="36" y="80" type="pin a[24:0]" />
         <line x2="32" y1="112" y2="112" style="linewidth:W" x1="0" />
-        <attrtext style="fontsize:24;fontname:Arial" attrname="PinName" x="36" y="112" type="pin b[20:0]" />
+        <attrtext style="fontsize:24;fontname:Arial" attrname="PinName" x="36" y="112" type="pin b[24:0]" />
         <line x2="32" y1="144" y2="144" x1="0" />
         <attrtext style="fontsize:24;fontname:Arial" attrname="PinName" x="36" y="144" type="pin clk" />
         <line x2="32" y1="208" y2="208" x1="0" />
diff --git a/stitch_project/stitch/ipcore_dir/multiaddCos.vhd b/stitch_project/stitch/ipcore_dir/multiaddCos.vhd
index 79f6c3020881fb1c6dc23073e5027029c993fe61..1e5dcab62c0e87b8e5dee2cb78a80de936640c7a 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddCos.vhd
+++ b/stitch_project/stitch/ipcore_dir/multiaddCos.vhd
@@ -46,8 +46,8 @@ ENTITY multiaddCos IS
     ce : IN STD_LOGIC;
     sclr : IN STD_LOGIC;
     bypass : IN STD_LOGIC;
-    a : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
-    b : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
+    a : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
+    b : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
     s : OUT STD_LOGIC_VECTOR(69 DOWNTO 0)
   );
 END multiaddCos;
@@ -60,8 +60,8 @@ COMPONENT wrapped_multiaddCos
     ce : IN STD_LOGIC;
     sclr : IN STD_LOGIC;
     bypass : IN STD_LOGIC;
-    a : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
-    b : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
+    a : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
+    b : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
     s : OUT STD_LOGIC_VECTOR(69 DOWNTO 0)
   );
 END COMPONENT;
@@ -70,11 +70,11 @@ END COMPONENT;
   FOR ALL : wrapped_multiaddCos USE ENTITY XilinxCoreLib.xbip_multaccum_v2_0(behavioral)
     GENERIC MAP (
       c_a_type => 0,
-      c_a_width => 21,
+      c_a_width => 25,
       c_accum_mode => 0,
       c_accum_width => 70,
-      c_b_type => 1,
-      c_b_width => 21,
+      c_b_type => 0,
+      c_b_width => 25,
       c_bypass_low => 0,
       c_ce_overrides_sclr => 0,
       c_has_bypass => 1,
diff --git a/stitch_project/stitch/ipcore_dir/multiaddCos.vho b/stitch_project/stitch/ipcore_dir/multiaddCos.vho
index fa0239fd23eb665d6293321d5d4948d04876af4c..d001b3a22173acd206758afc705ad50d2f35011b 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddCos.vho
+++ b/stitch_project/stitch/ipcore_dir/multiaddCos.vho
@@ -54,8 +54,8 @@ COMPONENT multiaddCos
     ce : IN STD_LOGIC;
     sclr : IN STD_LOGIC;
     bypass : IN STD_LOGIC;
-    a : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
-    b : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
+    a : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
+    b : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
     s : OUT STD_LOGIC_VECTOR(69 DOWNTO 0)
   );
 END COMPONENT;
diff --git a/stitch_project/stitch/ipcore_dir/multiaddCos.xco b/stitch_project/stitch/ipcore_dir/multiaddCos.xco
index b3fb2608510b0af176576759b73aea70dd8890cf..f46676ef1837decf8ffec55d8dfc2ddcb3ce5074 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddCos.xco
+++ b/stitch_project/stitch/ipcore_dir/multiaddCos.xco
@@ -1,7 +1,7 @@
 ##############################################################
 #
 # Xilinx Core Generator version 14.7
-# Date: Sat Jun 29 02:24:22 2024
+# Date: Sat Jun 29 15:36:39 2024
 #
 ##############################################################
 #
@@ -40,11 +40,11 @@ SELECT Multiply_Accumulator xilinx.com:ip:xbip_multaccum:2.0
 # END Select
 # BEGIN Parameters
 CSET a_input_type=Signed
-CSET a_input_width=21
+CSET a_input_width=25
 CSET accum_mode=Add
 CSET accum_width=70
-CSET b_input_type=Unsigned
-CSET b_input_width=21
+CSET b_input_type=Signed
+CSET b_input_width=25
 CSET bypass=true
 CSET bypass_sense=Active_High
 CSET component_name=multiaddCos
@@ -58,4 +58,4 @@ CSET sync_ce_priority=Sync_Overrides_CE
 MISC pkg_timestamp=2013-07-22T10:40:50Z
 # END Extra information
 GENERATE
-# CRC: f238e4b7
+# CRC: 95dccc0b
diff --git a/stitch_project/stitch/ipcore_dir/multiaddCos.xise b/stitch_project/stitch/ipcore_dir/multiaddCos.xise
index ad567485c930c2ed73df88d54aaa519cd1bc8dda..5539ccf0e588429d444098d9bb5fedca9fb810d4 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddCos.xise
+++ b/stitch_project/stitch/ipcore_dir/multiaddCos.xise
@@ -51,8 +51,8 @@
     <!--                                                                                  -->
     <property xil_pn:name="PROP_DesignName" xil_pn:value="multiaddCos" xil_pn:valueState="non-default"/>
     <property xil_pn:name="PROP_DevFamilyPMName" xil_pn:value="spartan6" xil_pn:valueState="default"/>
-    <property xil_pn:name="PROP_intProjectCreationTimestamp" xil_pn:value="2024-06-29T02:24:42" xil_pn:valueState="non-default"/>
-    <property xil_pn:name="PROP_intWbtProjectID" xil_pn:value="E84F04CE90CDF57F8F2EBF92C43212BC" xil_pn:valueState="non-default"/>
+    <property xil_pn:name="PROP_intProjectCreationTimestamp" xil_pn:value="2024-06-29T15:37:00" xil_pn:valueState="non-default"/>
+    <property xil_pn:name="PROP_intWbtProjectID" xil_pn:value="0A474FF2F2837F073C2B933E7659038D" xil_pn:valueState="non-default"/>
     <property xil_pn:name="PROP_intWorkingDirLocWRTProjDir" xil_pn:value="Same" xil_pn:valueState="non-default"/>
     <property xil_pn:name="PROP_intWorkingDirUsed" xil_pn:value="No" xil_pn:valueState="non-default"/>
   </properties>
diff --git a/stitch_project/stitch/ipcore_dir/multiaddSin.asy b/stitch_project/stitch/ipcore_dir/multiaddSin.asy
index 59bea4507be037b95e411cc7e498ba799e72ccb7..1d017ce6ea17c5894f2c929847ef86e1bfe27441 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddSin.asy
+++ b/stitch_project/stitch/ipcore_dir/multiaddSin.asy
@@ -4,11 +4,11 @@ TEXT 32 32 LEFT 4 multiaddSin
 RECTANGLE Normal 32 32 256 320
 LINE Wide 0 80 32 80
 PIN 0 80 LEFT 36
-PINATTR PinName a[20:0]
+PINATTR PinName a[24:0]
 PINATTR Polarity IN
 LINE Wide 0 112 32 112
 PIN 0 112 LEFT 36
-PINATTR PinName b[20:0]
+PINATTR PinName b[24:0]
 PINATTR Polarity IN
 LINE Normal 0 144 32 144
 PIN 0 144 LEFT 36
diff --git a/stitch_project/stitch/ipcore_dir/multiaddSin.gise b/stitch_project/stitch/ipcore_dir/multiaddSin.gise
index b8798cf957e5aeef7265f073ee6f73554dd3e32a..d791298ee243f5a03eb6d3ca17f0eba423675989 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddSin.gise
+++ b/stitch_project/stitch/ipcore_dir/multiaddSin.gise
@@ -34,19 +34,19 @@
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="1669001868035964362" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="1669001868035964362" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="-3351964163447721734" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="-3351964163447721734" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="-5480484674542449268" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="-5480484674542449268" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
diff --git a/stitch_project/stitch/ipcore_dir/multiaddSin.ngc b/stitch_project/stitch/ipcore_dir/multiaddSin.ngc
index 8f8020db22ca9c2ba77006c1b4aa8523768e3181..cd0f9d0421149b896a452a773f03ba5f67098958 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddSin.ngc
+++ b/stitch_project/stitch/ipcore_dir/multiaddSin.ngc
@@ -1,3 +1,3 @@
 XILINX-XDB 0.1 STUB 0.1 ASCII
 XILINX-XDM V1.6e
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diff --git a/stitch_project/stitch/ipcore_dir/multiaddSin.sym b/stitch_project/stitch/ipcore_dir/multiaddSin.sym
index 73796566bffbe667ba81f44cb42e49bd057e9cf0..4b00b1f84005088f660e50854c47ceddaa547da9 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddSin.sym
+++ b/stitch_project/stitch/ipcore_dir/multiaddSin.sym
@@ -1,9 +1,9 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <symbol version="7" name="multiaddSin">
     <symboltype>BLOCK</symboltype>
-    <timestamp>2024-8-29T8:47:28</timestamp>
-    <pin polarity="Input" x="0" y="80" name="a[20:0]" />
-    <pin polarity="Input" x="0" y="112" name="b[20:0]" />
+    <timestamp>2024-9-10T14:35:22</timestamp>
+    <pin polarity="Input" x="0" y="80" name="a[24:0]" />
+    <pin polarity="Input" x="0" y="112" name="b[24:0]" />
     <pin polarity="Input" x="0" y="144" name="clk" />
     <pin polarity="Input" x="0" y="208" name="ce" />
     <pin polarity="Input" x="0" y="240" name="bypass" />
@@ -13,9 +13,9 @@
         <text style="fontsize:40;fontname:Arial" x="32" y="32">multiaddSin</text>
         <rect width="224" x="32" y="32" height="288" />
         <line x2="32" y1="80" y2="80" style="linewidth:W" x1="0" />
-        <attrtext style="fontsize:24;fontname:Arial" attrname="PinName" x="36" y="80" type="pin a[20:0]" />
+        <attrtext style="fontsize:24;fontname:Arial" attrname="PinName" x="36" y="80" type="pin a[24:0]" />
         <line x2="32" y1="112" y2="112" style="linewidth:W" x1="0" />
-        <attrtext style="fontsize:24;fontname:Arial" attrname="PinName" x="36" y="112" type="pin b[20:0]" />
+        <attrtext style="fontsize:24;fontname:Arial" attrname="PinName" x="36" y="112" type="pin b[24:0]" />
         <line x2="32" y1="144" y2="144" x1="0" />
         <attrtext style="fontsize:24;fontname:Arial" attrname="PinName" x="36" y="144" type="pin clk" />
         <line x2="32" y1="208" y2="208" x1="0" />
diff --git a/stitch_project/stitch/ipcore_dir/multiaddSin.vhd b/stitch_project/stitch/ipcore_dir/multiaddSin.vhd
index 93a57808cd9b4cd51cc903b164328415f9fc07b1..7a62c510ba09c280bdb75323b2d974ea0404afee 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddSin.vhd
+++ b/stitch_project/stitch/ipcore_dir/multiaddSin.vhd
@@ -46,8 +46,8 @@ ENTITY multiaddSin IS
     ce : IN STD_LOGIC;
     sclr : IN STD_LOGIC;
     bypass : IN STD_LOGIC;
-    a : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
-    b : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
+    a : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
+    b : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
     s : OUT STD_LOGIC_VECTOR(69 DOWNTO 0)
   );
 END multiaddSin;
@@ -60,8 +60,8 @@ COMPONENT wrapped_multiaddSin
     ce : IN STD_LOGIC;
     sclr : IN STD_LOGIC;
     bypass : IN STD_LOGIC;
-    a : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
-    b : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
+    a : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
+    b : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
     s : OUT STD_LOGIC_VECTOR(69 DOWNTO 0)
   );
 END COMPONENT;
@@ -70,11 +70,11 @@ END COMPONENT;
   FOR ALL : wrapped_multiaddSin USE ENTITY XilinxCoreLib.xbip_multaccum_v2_0(behavioral)
     GENERIC MAP (
       c_a_type => 0,
-      c_a_width => 21,
+      c_a_width => 25,
       c_accum_mode => 0,
       c_accum_width => 70,
-      c_b_type => 1,
-      c_b_width => 21,
+      c_b_type => 0,
+      c_b_width => 25,
       c_bypass_low => 0,
       c_ce_overrides_sclr => 0,
       c_has_bypass => 1,
diff --git a/stitch_project/stitch/ipcore_dir/multiaddSin.vho b/stitch_project/stitch/ipcore_dir/multiaddSin.vho
index a0551a7cca6a13fb09e49ab0d6f2888c72d4e51f..6abf8fd1b545e373a2d8be83bbe385b0af0f0f52 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddSin.vho
+++ b/stitch_project/stitch/ipcore_dir/multiaddSin.vho
@@ -54,8 +54,8 @@ COMPONENT multiaddSin
     ce : IN STD_LOGIC;
     sclr : IN STD_LOGIC;
     bypass : IN STD_LOGIC;
-    a : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
-    b : IN STD_LOGIC_VECTOR(20 DOWNTO 0);
+    a : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
+    b : IN STD_LOGIC_VECTOR(24 DOWNTO 0);
     s : OUT STD_LOGIC_VECTOR(69 DOWNTO 0)
   );
 END COMPONENT;
diff --git a/stitch_project/stitch/ipcore_dir/multiaddSin.xco b/stitch_project/stitch/ipcore_dir/multiaddSin.xco
index b76bf97182e16637a5a96dd669a9e11de7044564..33bdafe3e2694973d1da4bd336b1964482c69cdc 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddSin.xco
+++ b/stitch_project/stitch/ipcore_dir/multiaddSin.xco
@@ -1,7 +1,7 @@
 ##############################################################
 #
 # Xilinx Core Generator version 14.7
-# Date: Sat Jun 29 02:23:50 2024
+# Date: Sat Jun 29 15:35:41 2024
 #
 ##############################################################
 #
@@ -40,11 +40,11 @@ SELECT Multiply_Accumulator xilinx.com:ip:xbip_multaccum:2.0
 # END Select
 # BEGIN Parameters
 CSET a_input_type=Signed
-CSET a_input_width=21
+CSET a_input_width=25
 CSET accum_mode=Add
 CSET accum_width=70
-CSET b_input_type=Unsigned
-CSET b_input_width=21
+CSET b_input_type=Signed
+CSET b_input_width=25
 CSET bypass=true
 CSET bypass_sense=Active_High
 CSET component_name=multiaddSin
@@ -58,4 +58,4 @@ CSET sync_ce_priority=Sync_Overrides_CE
 MISC pkg_timestamp=2013-07-22T10:40:50Z
 # END Extra information
 GENERATE
-# CRC: d37ce732
+# CRC: b498cf8e
diff --git a/stitch_project/stitch/ipcore_dir/multiaddSin.xise b/stitch_project/stitch/ipcore_dir/multiaddSin.xise
index bb7aa988a355e52c87e29702968c732a988e9942..2ed7e4714c6ac5b4adba6aa2dcd16b9bca481cff 100644
--- a/stitch_project/stitch/ipcore_dir/multiaddSin.xise
+++ b/stitch_project/stitch/ipcore_dir/multiaddSin.xise
@@ -51,8 +51,8 @@
     <!--                                                                                  -->
     <property xil_pn:name="PROP_DesignName" xil_pn:value="multiaddSin" xil_pn:valueState="non-default"/>
     <property xil_pn:name="PROP_DevFamilyPMName" xil_pn:value="spartan6" xil_pn:valueState="default"/>
-    <property xil_pn:name="PROP_intProjectCreationTimestamp" xil_pn:value="2024-06-29T02:24:10" xil_pn:valueState="non-default"/>
-    <property xil_pn:name="PROP_intWbtProjectID" xil_pn:value="E84A71DDB4A714D3E4034AEEEA7A158D" xil_pn:valueState="non-default"/>
+    <property xil_pn:name="PROP_intProjectCreationTimestamp" xil_pn:value="2024-06-29T15:36:02" xil_pn:valueState="non-default"/>
+    <property xil_pn:name="PROP_intWbtProjectID" xil_pn:value="D6428D21B47E9E0333F26D89EF8466A5" xil_pn:valueState="non-default"/>
     <property xil_pn:name="PROP_intWorkingDirLocWRTProjDir" xil_pn:value="Same" xil_pn:valueState="non-default"/>
     <property xil_pn:name="PROP_intWorkingDirUsed" xil_pn:value="No" xil_pn:valueState="non-default"/>
   </properties>
diff --git a/stitch_project/stitch/ipcore_dir/tmp/_xmsgs/xst.xmsgs b/stitch_project/stitch/ipcore_dir/tmp/_xmsgs/xst.xmsgs
index 0319b8bd0213e2023d2d528b853e6b024f680fe7..03f30bc72622a72b6dadcbd9f84a0f279605cfe2 100644
--- a/stitch_project/stitch/ipcore_dir/tmp/_xmsgs/xst.xmsgs
+++ b/stitch_project/stitch/ipcore_dir/tmp/_xmsgs/xst.xmsgs
@@ -56,6 +56,9 @@
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;59&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;59&gt;</arg> signal will be lost.
 </msg>
 
+<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;58&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;58&gt;</arg> signal will be lost.
+</msg>
+
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;34&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;34&gt;</arg> signal will be lost.
 </msg>
 
@@ -71,9 +74,6 @@
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;30&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;30&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;58&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;58&gt;</arg> signal will be lost.
-</msg>
-
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;29&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;29&gt;</arg> signal will be lost.
 </msg>
 
@@ -83,6 +83,9 @@
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;27&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;27&gt;</arg> signal will be lost.
 </msg>
 
+<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;57&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;57&gt;</arg> signal will be lost.
+</msg>
+
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;26&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;26&gt;</arg> signal will be lost.
 </msg>
 
@@ -104,9 +107,6 @@
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;20&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;20&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;57&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;57&gt;</arg> signal will be lost.
-</msg>
-
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;19&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;19&gt;</arg> signal will be lost.
 </msg>
 
@@ -116,37 +116,16 @@
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;17&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;17&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;16&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;16&gt;</arg> signal will be lost.
-</msg>
-
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;15&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;15&gt;</arg> signal will be lost.
-</msg>
-
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;14&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;14&gt;</arg> signal will be lost.
-</msg>
-
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;13&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;13&gt;</arg> signal will be lost.
-</msg>
-
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;12&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;12&gt;</arg> signal will be lost.
-</msg>
-
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;11&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;11&gt;</arg> signal will be lost.
-</msg>
-
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;10&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;10&gt;</arg> signal will be lost.
-</msg>
-
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;56&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;56&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;9&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;9&gt;</arg> signal will be lost.
+<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;16&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;16&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;8&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;8&gt;</arg> signal will be lost.
+<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;15&gt;</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;15&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;7&gt;1</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;7&gt;1</arg> signal will be lost.
+<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext_i&lt;2&gt;&lt;14&gt;1</arg> <arg fmt="%s" index="4">b_ext_i&lt;2&gt;&lt;14&gt;1</arg> signal will be lost.
 </msg>
 
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;55&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;55&gt;</arg> signal will be lost.
@@ -173,25 +152,25 @@
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;49&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;49&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;48&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;48&gt;</arg> signal will be lost.
+<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext_i&lt;2&gt;&lt;13&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;48&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;48&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;47&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;47&gt;</arg> signal will be lost.
+<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext_i&lt;2&gt;&lt;12&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;47&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;47&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;46&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;46&gt;</arg> signal will be lost.
+<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext_i&lt;2&gt;&lt;11&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;46&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;46&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;45&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;45&gt;</arg> signal will be lost.
+<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext_i&lt;2&gt;&lt;10&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;45&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;45&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;44&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;44&gt;</arg> signal will be lost.
+<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext_i&lt;2&gt;&lt;9&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;44&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;44&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;43&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;43&gt;</arg> signal will be lost.
+<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext_i&lt;2&gt;&lt;8&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;43&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;43&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext&lt;69&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;42&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;42&gt;</arg> signal will be lost.
+<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext_i&lt;2&gt;&lt;7&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;42&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;42&gt;</arg> signal will be lost.
 </msg>
 
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">fabric_piped_accum</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">b_ext_i&lt;2&gt;&lt;6&gt;</arg> and <arg fmt="%s" index="3">b_ext&lt;41&gt;</arg> <arg fmt="%s" index="4">b_ext&lt;41&gt;</arg> signal will be lost.
@@ -734,27 +713,6 @@
 <msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">U0/i_synth</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;15&gt;</arg> and <arg fmt="%s" index="3">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;14&gt;</arg> <arg fmt="%s" index="4">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;14&gt;</arg> signal will be lost.
 </msg>
 
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">U0/i_synth</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;14&gt;</arg> and <arg fmt="%s" index="3">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;13&gt;</arg> <arg fmt="%s" index="4">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;13&gt;</arg> signal will be lost.
-</msg>
-
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">U0/i_synth</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;13&gt;</arg> and <arg fmt="%s" index="3">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;12&gt;</arg> <arg fmt="%s" index="4">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;12&gt;</arg> signal will be lost.
-</msg>
-
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">U0/i_synth</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;12&gt;</arg> and <arg fmt="%s" index="3">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;11&gt;</arg> <arg fmt="%s" index="4">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;11&gt;</arg> signal will be lost.
-</msg>
-
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">U0/i_synth</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;11&gt;</arg> and <arg fmt="%s" index="3">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;10&gt;</arg> <arg fmt="%s" index="4">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;10&gt;</arg> signal will be lost.
-</msg>
-
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">U0/i_synth</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;10&gt;</arg> and <arg fmt="%s" index="3">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;9&gt;</arg> <arg fmt="%s" index="4">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;9&gt;</arg> signal will be lost.
-</msg>
-
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">U0/i_synth</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;10&gt;</arg> and <arg fmt="%s" index="3">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;8&gt;</arg> <arg fmt="%s" index="4">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;8&gt;</arg> signal will be lost.
-</msg>
-
-<msg type="warning" file="Xst" num="638" delta="old" >in unit <arg fmt="%s" index="1">U0/i_synth</arg> Conflict on KEEP property on signal <arg fmt="%s" index="2">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;10&gt;</arg> and <arg fmt="%s" index="3">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;7&gt;</arg> <arg fmt="%s" index="4">dsp_implementation.use_multaccum_dsp/i_sp3adsp.mult_accum_implementation.accum_inst/piped_fabric_implementation.i_fab_pipe_accum/i_accum_seg[2].b_seg&lt;7&gt;</arg> signal will be lost.
-</msg>
-
 <msg type="info" file="Xst" num="2169" delta="old" >HDL ADVISOR - Some clock signals were not automatically buffered by XST with BUFG/BUFR resources. Please use the buffer_type constraint in order to insert these buffers to the clock signals to help prevent skew problems.
 </msg>
 
diff --git a/stitch_project/stitch/iseconfig/stitch.projectmgr b/stitch_project/stitch/iseconfig/stitch.projectmgr
index 118a5812e91271aecbb451307cfa59ff100ae1a9..75b4e17e5e62b3b94d949cbaad83b576620f2e1c 100644
--- a/stitch_project/stitch/iseconfig/stitch.projectmgr
+++ b/stitch_project/stitch/iseconfig/stitch.projectmgr
@@ -9,13 +9,13 @@
          <ClosedNodesVersion>2</ClosedNodesVersion>
       </ClosedNodes>
       <SelectedItems>
-         <SelectedItem>Stitch - Behavioral (/home/ise/iseprojects/stitch/stitch_project/stitch/Stitch.vhd)</SelectedItem>
+         <SelectedItem>iLockInAccumulator - LockInAccumulator - Behavioral (/home/ise/iseprojects/stitch/stitch_project/stitch/LockInAccumulator.vhd)</SelectedItem>
       </SelectedItems>
       <ScrollbarPosition orientation="vertical" >0</ScrollbarPosition>
       <ScrollbarPosition orientation="horizontal" >0</ScrollbarPosition>
       <ViewHeaderState orientation="horizontal" >000000ff00000000000000010000000100000000000000000000000000000000020200000001000000010000006400000259000000020000000000000000000000000200000064ffffffff000000810000000300000002000002590000000100000003000000000000000100000003</ViewHeaderState>
       <UserChangedColumnWidths orientation="horizontal" >true</UserChangedColumnWidths>
-      <CurrentItem>Stitch - Behavioral (/home/ise/iseprojects/stitch/stitch_project/stitch/Stitch.vhd)</CurrentItem>
+      <CurrentItem>iLockInAccumulator - LockInAccumulator - Behavioral (/home/ise/iseprojects/stitch/stitch_project/stitch/LockInAccumulator.vhd)</CurrentItem>
    </ItemView>
    <ItemView engineview="SynthesisOnly" sourcetype="" guiview="Process" >
       <ClosedNodes>
@@ -40,7 +40,7 @@
       </SelectedItems>
       <ScrollbarPosition orientation="vertical" >0</ScrollbarPosition>
       <ScrollbarPosition orientation="horizontal" >0</ScrollbarPosition>
-      <ViewHeaderState orientation="horizontal" >000000ff00000000000000010000000000000000010000000000000000000000000000000000000268000000040101000100000000000000000000000064ffffffff0000008100000000000000040000009400000001000000000000005d0000000100000000000000840000000100000000000000f30000000100000000</ViewHeaderState>
+      <ViewHeaderState orientation="horizontal" >000000ff000000000000000100000000000000000100000000000000000000000000000000000004df000000040101000100000000000000000000000064ffffffff0000008100000000000000040000009400000001000000000000005d00000001000000000000008400000001000000000000036a0000000100000000</ViewHeaderState>
       <UserChangedColumnWidths orientation="horizontal" >false</UserChangedColumnWidths>
       <CurrentItem>LaserReceiver.vhd</CurrentItem>
    </ItemView>
@@ -52,7 +52,7 @@
       <SelectedItems/>
       <ScrollbarPosition orientation="vertical" >0</ScrollbarPosition>
       <ScrollbarPosition orientation="horizontal" >0</ScrollbarPosition>
-      <ViewHeaderState orientation="horizontal" >000000ff00000000000000010000000000000000010000000000000000000000000000000000000268000000010001000100000000000000000000000064ffffffff000000810000000000000001000002680000000100000000</ViewHeaderState>
+      <ViewHeaderState orientation="horizontal" >000000ff00000000000000010000000000000000010000000000000000000000000000000000000128000000010001000100000000000000000000000064ffffffff000000810000000000000001000001280000000100000000</ViewHeaderState>
       <UserChangedColumnWidths orientation="horizontal" >false</UserChangedColumnWidths>
       <CurrentItem>work</CurrentItem>
    </ItemView>
@@ -73,9 +73,9 @@
       <SelectedItems>
          <SelectedItem></SelectedItem>
       </SelectedItems>
-      <ScrollbarPosition orientation="vertical" >12</ScrollbarPosition>
+      <ScrollbarPosition orientation="vertical" >0</ScrollbarPosition>
       <ScrollbarPosition orientation="horizontal" >0</ScrollbarPosition>
-      <ViewHeaderState orientation="horizontal" >000000ff00000000000000010000000100000000000000000000000000000000000000000000000259000000010000000100000000000000000000000064ffffffff000000810000000000000001000002590000000100000000</ViewHeaderState>
+      <ViewHeaderState orientation="horizontal" >000000ff00000000000000010000000100000000000000000000000000000000000000000000000268000000010000000100000000000000000000000064ffffffff000000810000000000000001000002680000000100000000</ViewHeaderState>
       <UserChangedColumnWidths orientation="horizontal" >false</UserChangedColumnWidths>
       <CurrentItem></CurrentItem>
    </ItemView>
diff --git a/stitch_project/stitch/stitch.gise b/stitch_project/stitch/stitch.gise
index b670977d52d64d21d1dd2096dbb1d5386da16f0e..50ede3569007cec6a47d0e44d47edd611758c530 100644
--- a/stitch_project/stitch/stitch.gise
+++ b/stitch_project/stitch/stitch.gise
@@ -137,15 +137,15 @@
   </files>
 
   <transforms xmlns="http://www.xilinx.com/XMLSchema">
-    <transform xil_pn:end_ts="1719654152" xil_pn:name="TRAN_copyInitialToXSTAbstractSynthesis" xil_pn:start_ts="1719654152">
+    <transform xil_pn:end_ts="1726124436" xil_pn:name="TRAN_copyInitialToXSTAbstractSynthesis" xil_pn:start_ts="1726124436">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654152" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="-1000327047199651568" xil_pn:start_ts="1719654152">
+    <transform xil_pn:end_ts="1726124436" xil_pn:name="TRAN_schematicsToHdl" xil_pn:prop_ck="-1000327047199651568" xil_pn:start_ts="1726124436">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:in_ck="-759697606739902482" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="-2646617551451894976" xil_pn:start_ts="1719654152">
+    <transform xil_pn:end_ts="1726124439" xil_pn:in_ck="-759697606739902482" xil_pn:name="TRAN_regenerateCores" xil_pn:prop_ck="-2646617551451894976" xil_pn:start_ts="1726124436">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
       <outfile xil_pn:name="ipcore_dir/Mem32b1024.ngc"/>
@@ -161,28 +161,30 @@
       <outfile xil_pn:name="ipcore_dir/multiaddSin.ngc"/>
       <outfile xil_pn:name="ipcore_dir/multiaddSin.vhd"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:in_ck="6231951733186561032" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:in_ck="6231951733186561032" xil_pn:name="TRAN_SubProjectAbstractToPreProxy" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="-7265130963783582190" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_xawsTohdl" xil_pn:prop_ck="-7265130963783582190" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:in_ck="6231951733186561032" xil_pn:name="TRAN_SubProjectPreToStructuralProxy" xil_pn:prop_ck="8977612015756273942" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:in_ck="6231951733186561032" xil_pn:name="TRAN_SubProjectPreToStructuralProxy" xil_pn:prop_ck="8977612015756273942" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654154" xil_pn:name="TRAN_platgen" xil_pn:prop_ck="-3892313077777873078" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124439" xil_pn:name="TRAN_platgen" xil_pn:prop_ck="-3892313077777873078" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654163" xil_pn:in_ck="5188678245468887340" xil_pn:name="TRANEXT_xstsynthesize_spartan6" xil_pn:prop_ck="-6684372598054868263" xil_pn:start_ts="1719654154">
+    <transform xil_pn:end_ts="1726124519" xil_pn:in_ck="-2009185075857292629" xil_pn:name="TRANEXT_xstsynthesize_spartan6" xil_pn:prop_ck="-6684372598054868263" xil_pn:start_ts="1726124439">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="WarningsGenerated"/>
       <status xil_pn:value="ReadyToRun"/>
       <status xil_pn:value="OutOfDateForOutputs"/>
       <status xil_pn:value="OutputChanged"/>
+      <outfile xil_pn:name="CommandDecoder.ngr"/>
+      <outfile xil_pn:name="ReadbackControl.ngr"/>
       <outfile xil_pn:name="Stitch.lso"/>
       <outfile xil_pn:name="Stitch.ngc"/>
       <outfile xil_pn:name="Stitch.ngr"/>
@@ -191,15 +193,16 @@
       <outfile xil_pn:name="Stitch.syr"/>
       <outfile xil_pn:name="Stitch.xst"/>
       <outfile xil_pn:name="Stitch_xst.xrpt"/>
+      <outfile xil_pn:name="Sweeper.ngr"/>
       <outfile xil_pn:name="_xmsgs/xst.xmsgs"/>
       <outfile xil_pn:name="webtalk_pn.xml"/>
       <outfile xil_pn:name="xst"/>
     </transform>
-    <transform xil_pn:end_ts="1719654163" xil_pn:in_ck="5505092852261115" xil_pn:name="TRAN_compileBCD2" xil_pn:prop_ck="-3812858228316398073" xil_pn:start_ts="1719654163">
+    <transform xil_pn:end_ts="1726124519" xil_pn:in_ck="5505092852261115" xil_pn:name="TRAN_compileBCD2" xil_pn:prop_ck="-3812858228316398073" xil_pn:start_ts="1726124519">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
     </transform>
-    <transform xil_pn:end_ts="1719654167" xil_pn:in_ck="-9033868516707283598" xil_pn:name="TRANEXT_ngdbuild_FPGA" xil_pn:prop_ck="230146358404850379" xil_pn:start_ts="1719654163">
+    <transform xil_pn:end_ts="1726124539" xil_pn:in_ck="3802728747819461154" xil_pn:name="TRANEXT_ngdbuild_FPGA" xil_pn:prop_ck="230146358404850379" xil_pn:start_ts="1726124519">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
       <outfile xil_pn:name="Stitch.bld"/>
@@ -208,7 +211,7 @@
       <outfile xil_pn:name="_ngo"/>
       <outfile xil_pn:name="_xmsgs/ngdbuild.xmsgs"/>
     </transform>
-    <transform xil_pn:end_ts="1719654184" xil_pn:in_ck="-4325218870543059951" xil_pn:name="TRANEXT_map_spartan6" xil_pn:prop_ck="-398923363910175968" xil_pn:start_ts="1719654167">
+    <transform xil_pn:end_ts="1726124653" xil_pn:in_ck="-3282794330040821884" xil_pn:name="TRANEXT_map_spartan6" xil_pn:prop_ck="-398923363910175968" xil_pn:start_ts="1726124539">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="WarningsGenerated"/>
       <status xil_pn:value="ReadyToRun"/>
@@ -222,7 +225,7 @@
       <outfile xil_pn:name="Stitch_usage.xml"/>
       <outfile xil_pn:name="_xmsgs/map.xmsgs"/>
     </transform>
-    <transform xil_pn:end_ts="1719654204" xil_pn:in_ck="-6627939747938971286" xil_pn:name="TRANEXT_par_spartan6" xil_pn:prop_ck="-3829590541433901613" xil_pn:start_ts="1719654184">
+    <transform xil_pn:end_ts="1726124766" xil_pn:in_ck="-8255871056631862401" xil_pn:name="TRANEXT_par_spartan6" xil_pn:prop_ck="-3829590541433901613" xil_pn:start_ts="1726124653">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
       <outfile xil_pn:name="Stitch.ncd"/>
@@ -236,7 +239,7 @@
       <outfile xil_pn:name="Stitch_par.xrpt"/>
       <outfile xil_pn:name="_xmsgs/par.xmsgs"/>
     </transform>
-    <transform xil_pn:end_ts="1719654210" xil_pn:in_ck="4019925351390994" xil_pn:name="TRANEXT_bitFile_spartan6" xil_pn:prop_ck="4970201210546912173" xil_pn:start_ts="1719654204">
+    <transform xil_pn:end_ts="1726124805" xil_pn:in_ck="6552744863914881674" xil_pn:name="TRANEXT_bitFile_spartan6" xil_pn:prop_ck="4970201210546912173" xil_pn:start_ts="1726124766">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="WarningsGenerated"/>
       <status xil_pn:value="ReadyToRun"/>
@@ -249,7 +252,7 @@
       <outfile xil_pn:name="webtalk.log"/>
       <outfile xil_pn:name="webtalk_pn.xml"/>
     </transform>
-    <transform xil_pn:end_ts="1719654204" xil_pn:in_ck="-4527387296597967219" xil_pn:name="TRAN_postRouteTrce" xil_pn:prop_ck="445577401284416184" xil_pn:start_ts="1719654199">
+    <transform xil_pn:end_ts="1726124766" xil_pn:in_ck="3901311056773105669" xil_pn:name="TRAN_postRouteTrce" xil_pn:prop_ck="445577401284416184" xil_pn:start_ts="1726124741">
       <status xil_pn:value="SuccessfullyRun"/>
       <status xil_pn:value="ReadyToRun"/>
       <outfile xil_pn:name="Stitch.twr"/>
diff --git a/stitch_project/stitch/stitch.xise b/stitch_project/stitch/stitch.xise
index a710882b254b0a7a452f658998a8a652aa9b398d..e5cf87e5237fee78bd23e7be2645d4194e595ae2 100644
--- a/stitch_project/stitch/stitch.xise
+++ b/stitch_project/stitch/stitch.xise
@@ -25,7 +25,7 @@
     </file>
     <file xil_pn:name="CommandDecoder.vhd" xil_pn:type="FILE_VHDL">
       <association xil_pn:name="BehavioralSimulation" xil_pn:seqID="72"/>
-      <association xil_pn:name="Implementation" xil_pn:seqID="13"/>
+      <association xil_pn:name="Implementation" xil_pn:seqID="14"/>
     </file>
     <file xil_pn:name="Sweeper.vhd" xil_pn:type="FILE_VHDL">
       <association xil_pn:name="BehavioralSimulation" xil_pn:seqID="73"/>
@@ -65,7 +65,7 @@
     </file>
     <file xil_pn:name="Stitch.vhd" xil_pn:type="FILE_VHDL">
       <association xil_pn:name="BehavioralSimulation" xil_pn:seqID="122"/>
-      <association xil_pn:name="Implementation" xil_pn:seqID="15"/>
+      <association xil_pn:name="Implementation" xil_pn:seqID="16"/>
     </file>
     <file xil_pn:name="SerialTransmitter.vhd" xil_pn:type="FILE_VHDL">
       <association xil_pn:name="BehavioralSimulation" xil_pn:seqID="123"/>
@@ -76,7 +76,11 @@
     </file>
     <file xil_pn:name="Beeper.vhd" xil_pn:type="FILE_VHDL">
       <association xil_pn:name="BehavioralSimulation" xil_pn:seqID="125"/>
-      <association xil_pn:name="Implementation" xil_pn:seqID="14"/>
+      <association xil_pn:name="Implementation" xil_pn:seqID="15"/>
+    </file>
+    <file xil_pn:name="DistanceUnwrapper.vhd" xil_pn:type="FILE_VHDL">
+      <association xil_pn:name="BehavioralSimulation" xil_pn:seqID="167"/>
+      <association xil_pn:name="Implementation" xil_pn:seqID="13"/>
     </file>
     <file xil_pn:name="ipcore_dir/multiaddSin.xise" xil_pn:type="FILE_COREGENISE">
       <association xil_pn:name="Implementation" xil_pn:seqID="0"/>
diff --git a/stitch_project/stitch/xst/work/work.vdbl b/stitch_project/stitch/xst/work/work.vdbl
index 3264e8c04b5ad7fd7e32900cebd652afdee13b83..83081686e373a2de7e5eedac8168e4463f63ef88 100644
Binary files a/stitch_project/stitch/xst/work/work.vdbl and b/stitch_project/stitch/xst/work/work.vdbl differ
diff --git a/stitch_project/stitch/xst/work/work.vdbx b/stitch_project/stitch/xst/work/work.vdbx
index 7ea3353216b9b81154275e40a42922b59eae7fe2..7c6bd99dbe7e7fd4a28593326bd1a3fd72ed5636 100644
Binary files a/stitch_project/stitch/xst/work/work.vdbx and b/stitch_project/stitch/xst/work/work.vdbx differ