diff --git a/Part1/PROJ_WIN/CIS565_PROJ_1.suo b/Part1/PROJ_WIN/CIS565_PROJ_1.suo
index ad46c84..1c69bb1 100644
Binary files a/Part1/PROJ_WIN/CIS565_PROJ_1.suo and b/Part1/PROJ_WIN/CIS565_PROJ_1.suo differ
diff --git a/Part1/PROJ_WIN/CIS565_PROJ_1/CIS565_PROJ_1.vcxproj b/Part1/PROJ_WIN/CIS565_PROJ_1/CIS565_PROJ_1.vcxproj
index 4c88226..a4dd6ea 100644
--- a/Part1/PROJ_WIN/CIS565_PROJ_1/CIS565_PROJ_1.vcxproj
+++ b/Part1/PROJ_WIN/CIS565_PROJ_1/CIS565_PROJ_1.vcxproj
@@ -30,7 +30,7 @@
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   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
   <ImportGroup Label="ExtensionSettings">
-    <Import Project="$(VCTargetsPath)\BuildCustomizations\CUDA 5.5.props" />
+    <Import Project="$(VCTargetsPath)\BuildCustomizations\CUDA 6.5.props" />
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@@ -62,7 +62,7 @@
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       <GenerateLineInfo>true</GenerateLineInfo>
       <HostDebugInfo>true</HostDebugInfo>
-      <CodeGeneration>compute_10,sm_10;compute_20,sm_20;compute_30,sm_30</CodeGeneration>
+      <CodeGeneration>compute_20,sm_20;compute_30,sm_30</CodeGeneration>
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@@ -95,7 +95,7 @@
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-      <CodeGeneration Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">compute_10,sm_10;compute_20,sm_20</CodeGeneration>
+      <CodeGeneration Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">compute_20,sm_20</CodeGeneration>
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@@ -114,6 +114,6 @@
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-    <Import Project="$(VCTargetsPath)\BuildCustomizations\CUDA 5.5.targets" />
+    <Import Project="$(VCTargetsPath)\BuildCustomizations\CUDA 6.5.targets" />
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 </Project>
\ No newline at end of file
diff --git a/Part1/PROJ_WIN/CIS565_PROJ_1/vc100.pdb b/Part1/PROJ_WIN/CIS565_PROJ_1/vc100.pdb
index b662f85..06d7067 100644
Binary files a/Part1/PROJ_WIN/CIS565_PROJ_1/vc100.pdb and b/Part1/PROJ_WIN/CIS565_PROJ_1/vc100.pdb differ
diff --git a/Part1/PROJ_WIN/src/kernel.cu.deps b/Part1/PROJ_WIN/src/kernel.cu.deps
index 926dd55..34545f0 100644
--- a/Part1/PROJ_WIN/src/kernel.cu.deps
+++ b/Part1/PROJ_WIN/src/kernel.cu.deps
@@ -1,568 +1,568 @@
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+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xfwrap1
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xxshared
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xfwrap1
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xxshared
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xfwrap1
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xxshared
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xfwrap1
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xxshared
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xfwrap1
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xxshared
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xfwrap1
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xxshared
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\istream
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\ostream
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\ios
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xlocnum
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\streambuf
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xiosbase
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xlocale
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\stdexcept
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xstring
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xlocinfo
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xlocinfo.h
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\ctype.h
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\crtdefs.h
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\locale.h
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\crtdefs.h
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xdebug
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\system_error
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\cerrno
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\errno.h
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\crtdefs.h
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\share.h
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\iterator
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\sstream
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\string
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\vector
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\xfunctional
+d:\documents\cis 565\project-1\part1\src\cudaMat4.h
+d:\documents\cis 565\project-1\part1\src\glm/glm.hpp
+d:\documents\cis 565\project-1\part1\src\glm\core/_fixes.hpp
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\cuda_runtime.h
+d:\documents\cis 565\project-1\part1\src\kernel.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/config.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/config/config.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/config/simple_defines.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/config/compiler.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\cuda.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/config/host_system.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/config/device_system.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/config/host_device.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\host_defines.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/config/debug.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/config/compiler_fence.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/config/forceinline.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/config/hd_warning_disable.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/config/global_workarounds.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/cstdint.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/discard_block_engine.h
+C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\include\iostream
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/random_core_access.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/discard_block_engine.inl
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/linear_congruential_engine.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/linear_congruential_engine_discard.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/mod.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/linear_congruential_engine.inl
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/linear_feedback_shift_engine.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/linear_feedback_shift_engine_wordmask.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/linear_feedback_shift_engine.inl
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/subtract_with_carry_engine.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/subtract_with_carry_engine.inl
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/xor_combine_engine.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/type_traits.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/type_traits/has_trivial_assign.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/xor_combine_engine_max.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/mpl/math.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/xor_combine_engine.inl
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/uniform_int_distribution.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/pair.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/pair.inl
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/swap.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/detail/integer_traits.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/uniform_int_distribution.inl
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/uniform_real_distribution.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/uniform_real_distribution.inl
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/normal_distribution.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/normal_distribution_base.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\thrust/random/detail/normal_distribution.inl
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\math_constants.h
+C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v6.5\include\cuda.h
diff --git a/Part1/src/kernel.cu b/Part1/src/kernel.cu
index ee9b9e5..002d758 100644
--- a/Part1/src/kernel.cu
+++ b/Part1/src/kernel.cu
@@ -9,8 +9,8 @@
 dim3 threadsPerBlock(blockSize);
 
 int numObjects;
-const float planetMass = 3e8;
 const __device__ float starMass = 5e10;
+const __device__ float planetMass = 3e8;
 
 const float scene_scale = 2e2; //size of the height map in simulation space
 
@@ -89,19 +89,37 @@ __global__ void generateCircularVelArray(int time, int N, glm::vec3 * arr, glm::
 //		 REMEMBER : F = (G * m_a * m_b) / (r_ab ^ 2)
 __device__  glm::vec3 accelerate(int N, glm::vec4 my_pos, glm::vec4 * their_pos)
 {
-    return glm::vec3(0.0f);
+	glm::vec3 delta_acc (0.f);
+	float dist_from_star = sqrt(my_pos.x * my_pos.x + my_pos.y * my_pos.y + my_pos.z * my_pos.z);
+	if (dist_from_star > 1) {
+		delta_acc += (float)(G * starMass) / pow(dist_from_star, 3) * (-glm::vec3(my_pos));
+	}
+	for (int i = 0; i < N; i++) {
+		//glm::vec3 their_pos_3d (their_pos[i]);
+		glm::vec3 R (their_pos[i] - my_pos);
+		float dist = sqrt(R.x * R.x + R.y * R.y + R.z * R.z);
+		if (dist > 1) {
+			delta_acc += (float)(G * planetMass) / pow(dist, 3) * R;
+		}
+	}
+	
+    return delta_acc;
 }
 
 // TODO : update the acceleration of each body
 __global__ void updateF(int N, float dt, glm::vec4 * pos, glm::vec3 * vel, glm::vec3 * acc)
 {
-	// FILL IN HERE
+	int index = threadIdx.x + (blockIdx.x * blockDim.x);
+	acc[index] = accelerate(N, pos[index], pos);
 }
 
 // TODO : update velocity and position using a simple Euler integration scheme
 __global__ void updateS(int N, float dt, glm::vec4 * pos, glm::vec3 * vel, glm::vec3 * acc)
 {
 	// FILL IN HERE
+    int index = threadIdx.x + (blockIdx.x * blockDim.x);
+	pos[index] += glm::vec4(dt * vel[index],0);
+	vel[index] += dt * acc[index];
 }
 
 // Update the vertex buffer object
@@ -180,6 +198,11 @@ void initCuda(int N)
 void cudaNBodyUpdateWrapper(float dt)
 {
 	// FILL IN HERE
+	dim3 fullBlocksPerGrid((int)ceil(float(numObjects)/float(blockSize)));
+	updateF<<<fullBlocksPerGrid, blockSize>>>(numObjects, dt, dev_pos, dev_vel, dev_acc);
+    cudaThreadSynchronize();
+	updateS<<<fullBlocksPerGrid, blockSize>>>(numObjects, dt, dev_pos, dev_vel, dev_acc);
+    cudaThreadSynchronize();
 }
 
 void cudaUpdateVBO(float * vbodptr, int width, int height)
diff --git a/Part1/src/main.cpp b/Part1/src/main.cpp
index ea86207..268699e 100644
--- a/Part1/src/main.cpp
+++ b/Part1/src/main.cpp
@@ -62,7 +62,7 @@ void runCuda()
     // execute the kernel
     cudaNBodyUpdateWrapper(DT);
 #if VISUALIZE == 1
-    cudaUpdatePBO(dptr, field_width, field_height);
+    //cudaUpdatePBO(dptr, field_width, field_height);
     cudaUpdateVBO(dptrvert, field_width, field_height);
 #endif
     // unmap buffer object
diff --git a/Part2/Part2.sln b/Part2/Part2.sln
new file mode 100644
index 0000000..5bf4289
--- /dev/null
+++ b/Part2/Part2.sln
@@ -0,0 +1,20 @@
+
+Microsoft Visual Studio Solution File, Format Version 11.00
+# Visual Studio 2010
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "Project-1_part-2", "Project-1_part-2\Project-1_part-2.vcxproj", "{B9F2B494-1DFB-43C4-A456-00C4DCF651F9}"
+EndProject
+Global
+	GlobalSection(SolutionConfigurationPlatforms) = preSolution
+		Debug|Win32 = Debug|Win32
+		Release|Win32 = Release|Win32
+	EndGlobalSection
+	GlobalSection(ProjectConfigurationPlatforms) = postSolution
+		{B9F2B494-1DFB-43C4-A456-00C4DCF651F9}.Debug|Win32.ActiveCfg = Debug|Win32
+		{B9F2B494-1DFB-43C4-A456-00C4DCF651F9}.Debug|Win32.Build.0 = Debug|Win32
+		{B9F2B494-1DFB-43C4-A456-00C4DCF651F9}.Release|Win32.ActiveCfg = Release|Win32
+		{B9F2B494-1DFB-43C4-A456-00C4DCF651F9}.Release|Win32.Build.0 = Release|Win32
+	EndGlobalSection
+	GlobalSection(SolutionProperties) = preSolution
+		HideSolutionNode = FALSE
+	EndGlobalSection
+EndGlobal
diff --git a/Part2/Project-1_part-2/Project-1_part-2.vcxproj b/Part2/Project-1_part-2/Project-1_part-2.vcxproj
new file mode 100644
index 0000000..94e3a47
--- /dev/null
+++ b/Part2/Project-1_part-2/Project-1_part-2.vcxproj
@@ -0,0 +1,81 @@
+<?xml version="1.0" encoding="utf-8"?>
+<Project DefaultTargets="Build" ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
+  <ItemGroup Label="ProjectConfigurations">
+    <ProjectConfiguration Include="Debug|Win32">
+      <Configuration>Debug</Configuration>
+      <Platform>Win32</Platform>
+    </ProjectConfiguration>
+    <ProjectConfiguration Include="Release|Win32">
+      <Configuration>Release</Configuration>
+      <Platform>Win32</Platform>
+    </ProjectConfiguration>
+  </ItemGroup>
+  <PropertyGroup Label="Globals">
+    <ProjectGuid>{B9F2B494-1DFB-43C4-A456-00C4DCF651F9}</ProjectGuid>
+    <RootNamespace>Project1_part2</RootNamespace>
+    <ProjectName>Part2</ProjectName>
+  </PropertyGroup>
+  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
+  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
+    <ConfigurationType>Application</ConfigurationType>
+    <UseDebugLibraries>true</UseDebugLibraries>
+    <CharacterSet>MultiByte</CharacterSet>
+  </PropertyGroup>
+  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
+    <ConfigurationType>Application</ConfigurationType>
+    <UseDebugLibraries>false</UseDebugLibraries>
+    <WholeProgramOptimization>true</WholeProgramOptimization>
+    <CharacterSet>MultiByte</CharacterSet>
+  </PropertyGroup>
+  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
+  <ImportGroup Label="ExtensionSettings">
+    <Import Project="$(VCTargetsPath)\BuildCustomizations\CUDA 6.5.props" />
+  </ImportGroup>
+  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
+    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+  </ImportGroup>
+  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
+    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+  </ImportGroup>
+  <PropertyGroup Label="UserMacros" />
+  <PropertyGroup />
+  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
+    <ClCompile>
+      <WarningLevel>Level3</WarningLevel>
+      <Optimization>Disabled</Optimization>
+    </ClCompile>
+    <Link>
+      <GenerateDebugInformation>true</GenerateDebugInformation>
+      <AdditionalDependencies>kernel32.lib;user32.lib;gdi32.lib;cudart.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
+    </Link>
+    <CudaCompile>
+      <CompileOut>$(ProjectDir)$(Platform)/$(Configuration)/%(Filename)%(Extension).obj</CompileOut>
+    </CudaCompile>
+    <CudaCompile>
+      <Include>$(CudaToolkitIncludeDir)</Include>
+    </CudaCompile>
+  </ItemDefinitionGroup>
+  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
+    <ClCompile>
+      <WarningLevel>Level3</WarningLevel>
+      <Optimization>MaxSpeed</Optimization>
+      <FunctionLevelLinking>true</FunctionLevelLinking>
+      <IntrinsicFunctions>true</IntrinsicFunctions>
+    </ClCompile>
+    <Link>
+      <GenerateDebugInformation>true</GenerateDebugInformation>
+      <EnableCOMDATFolding>true</EnableCOMDATFolding>
+      <OptimizeReferences>true</OptimizeReferences>
+    </Link>
+  </ItemDefinitionGroup>
+  <ItemGroup>
+    <CudaCompile Include="matrix_math.cu">
+      <CompileOut Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">$(ProjectDir)$(Platform)/$(Configuration)/%(Filename)%(Extension).obj</CompileOut>
+      <Include Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">$(CudaToolkitIncludeDir)</Include>
+    </CudaCompile>
+  </ItemGroup>
+  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
+  <ImportGroup Label="ExtensionTargets">
+    <Import Project="$(VCTargetsPath)\BuildCustomizations\CUDA 6.5.targets" />
+  </ImportGroup>
+</Project>
\ No newline at end of file
diff --git a/Part2/Project-1_part-2/Project-1_part-2.vcxproj.filters b/Part2/Project-1_part-2/Project-1_part-2.vcxproj.filters
new file mode 100644
index 0000000..f07abd3
--- /dev/null
+++ b/Part2/Project-1_part-2/Project-1_part-2.vcxproj.filters
@@ -0,0 +1,22 @@
+<?xml version="1.0" encoding="utf-8"?>
+<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
+  <ItemGroup>
+    <Filter Include="Source Files">
+      <UniqueIdentifier>{4FC737F1-C7A5-4376-A066-2A32D752A2FF}</UniqueIdentifier>
+      <Extensions>cpp;c;cc;cxx;def;odl;idl;hpj;bat;asm;asmx</Extensions>
+    </Filter>
+    <Filter Include="Header Files">
+      <UniqueIdentifier>{93995380-89BD-4b04-88EB-625FBE52EBFB}</UniqueIdentifier>
+      <Extensions>h;hpp;hxx;hm;inl;inc;xsd</Extensions>
+    </Filter>
+    <Filter Include="Resource Files">
+      <UniqueIdentifier>{67DA6AB6-F800-4c08-8B7A-83BB121AAD01}</UniqueIdentifier>
+      <Extensions>rc;ico;cur;bmp;dlg;rc2;rct;bin;rgs;gif;jpg;jpeg;jpe;resx;tiff;tif;png;wav;mfcribbon-ms</Extensions>
+    </Filter>
+  </ItemGroup>
+  <ItemGroup>
+    <CudaCompile Include="matrix_math.cu">
+      <Filter>Source Files</Filter>
+    </CudaCompile>
+  </ItemGroup>
+</Project>
\ No newline at end of file
diff --git a/Part2/Project-1_part-2/matrix_math.cu b/Part2/Project-1_part-2/matrix_math.cu
new file mode 100644
index 0000000..99da827
--- /dev/null
+++ b/Part2/Project-1_part-2/matrix_math.cu
@@ -0,0 +1,125 @@
+#include <stdio.h>
+#include <cuda.h>
+#include <cmath>
+#include <iostream>
+
+float cpu_array [25];
+float cpu_output_array [25];
+float *gpu_array_A;
+float *gpu_array_B;
+float *gpu_output_array;
+const int mat_width = 5;
+
+dim3 dimBlock(mat_width, mat_width);
+dim3 dimGrid(1, 1);
+
+void initCuda(int width) {
+	cudaMalloc((void**)&gpu_array_A, width*width*sizeof(float));
+	cudaMemcpy(gpu_array_A, cpu_array, width*width*sizeof(float), cudaMemcpyHostToDevice);
+
+	cudaMalloc((void**)&gpu_array_B, width*width*sizeof(float));
+	cudaMemcpy(gpu_array_B, cpu_array, width*width*sizeof(float), cudaMemcpyHostToDevice);
+
+	cudaMalloc((void**)&gpu_output_array, width*width*sizeof(float));
+}
+
+__global__ void mat_add (float* Ad, float* Bd, float* Pd, int width) {
+	int index = threadIdx.y * width + threadIdx.x;
+
+	Pd[index] = Ad[index] + Bd[index];
+}
+
+__global__ void mat_sub (float* Ad, float* Bd, float* Pd, int width) {
+	int index = threadIdx.y * width + threadIdx.x;
+
+	Pd[index] = Ad[index] - Bd[index];
+}
+
+__global__ void mat_mult (float* Ad, float* Bd, float* Pd, int width) {
+	int tx = threadIdx.x;
+	int ty = threadIdx.y;
+
+	float Pvalue = 0;
+
+	for (int k = 0; k < width; k++) {
+		Pvalue += Ad[ty * width + k] * Bd[k * width + tx];
+	}
+
+	Pd[ty * width + tx] = Pvalue;
+}
+
+void cpu_mat_add (float* A, float* B, float* P, int width) {
+	for (int i = 0; i < width; i++) {
+		for (int j = 0; j < width; j++) {
+			P[j * width + i] = A[j * width + i] + B[j * width + i];
+		}
+	}
+}
+
+void cpu_mat_sub (float* A, float* B, float* P, int width) {
+	for (int i = 0; i < width; i++) {
+		for (int j = 0; j < width; j++) {
+			P[j * width + i] = A[j * width + i] - B[j * width + i];
+		}
+	}
+}
+
+/***
+* Simple helper function for printing a matrix.
+***/
+void cpu_mat_mult (float* A, float* B, float* P, int width) {
+	for (int i = 0; i < width; i++) {
+		for (int j = 0; j < width; j++) {
+			float Psum = 0;
+			for (int k = 0; k < width; k++) {
+				Psum += A[j * width + k] * B[k * width + i];
+			}
+			P[j * width + i] = Psum;
+		}
+	}
+}
+
+/***
+* Simple helper function for printing a matrix.
+***/
+void printMatrix (float* M, int width) {
+	for (int i = 0; i < width; i++) {
+		for (int j = 0; j < width; j++) {
+			std::cout << cpu_output_array[i * width + j] << " ";
+		}
+		std::cout << std::endl;
+	}
+}
+
+int main(int argc, char** argv) {
+
+	for (int i = 0; i < 25; i++) {
+		cpu_array[i] = i;
+	}
+	
+	initCuda(mat_width);
+	
+	mat_add<<<dimGrid, dimBlock>>>(gpu_array_A, gpu_array_B, gpu_output_array, mat_width);
+	cudaMemcpy(cpu_output_array, gpu_output_array, mat_width*mat_width*sizeof(float), cudaMemcpyDeviceToHost);
+	printMatrix(cpu_output_array, mat_width);
+
+	cpu_mat_add(cpu_array, cpu_array, cpu_output_array, mat_width);
+	printMatrix(cpu_output_array, mat_width);
+
+	mat_sub<<<dimGrid, dimBlock>>>(gpu_array_A, gpu_array_B, gpu_output_array, mat_width);
+	cudaMemcpy(cpu_output_array, gpu_output_array, mat_width*mat_width*sizeof(float), cudaMemcpyDeviceToHost);
+	printMatrix(cpu_output_array, mat_width);
+
+	cpu_mat_sub(cpu_array, cpu_array, cpu_output_array, mat_width);
+	printMatrix(cpu_output_array, mat_width);
+
+	mat_mult<<<dimGrid, dimBlock>>>(gpu_array_A, gpu_array_B, gpu_output_array, mat_width);
+	cudaMemcpy(cpu_output_array, gpu_output_array, mat_width*mat_width*sizeof(float), cudaMemcpyDeviceToHost);
+	printMatrix(cpu_output_array, mat_width);
+
+	cpu_mat_mult(cpu_array, cpu_array, cpu_output_array, mat_width);
+	printMatrix(cpu_output_array, mat_width);
+
+	int a;
+	std::cin>>a;
+}
\ No newline at end of file
diff --git a/README.md b/README.md
index 70ae0d3..7680160 100644
--- a/README.md
+++ b/README.md
@@ -1,120 +1,31 @@
-Project 1
+Project 1 Writeup
 =========
 
-# Project 1 : Introduction to CUDA
-
-## NOTE :
-This project (and all other projects in this course) requires a NVIDIA graphics
-card with CUDA capabilityi!  Any card with compute capability 2.0 and up will
-work.  This means any card from the GeForce 400 and 500 series and afterwards
-will work.  If you do not have a machine with these specs, feel free to use
-computers in the SIG Lab.  All computers in SIG lab and Moore 100 C have CUDA 
-capable cards and should already have the CUDA SDK installed. 
-
-## PART 1 : INSTALL NSIGHT
-To help with benchmarking and performance analysis, we will be using NVIDIA's
-profiling and debugging tool named NSight. Download and install it from the
-following link for whichever IDE you will be using:
-http://www.nvidia.com/object/nsight.html. 
-
-NOTE : If you are using Linux / Mac, most of the screenshots and class usage of
-NSight will be in Visual Studio.  You are free to use to the Eclipse version
-NSight during these in class labs, but we will not be able to help you as much.
-
-## PART 2 : NBODY SIMULATION
-To get you used to using CUDA kernels, we will be writing a simple 2D nbody 
-simulator.  The following source files are included in the project:
-
-* main.cpp : sets up graphics stuff for visualization
-* kernel.cu : this contains the CUDA kernel calls
-
-All the code that you will need to modify is in kernel.cu and is marked clearly
-by TODOs.
-
-## PART 3 : MATRIX MATH
-In this portion we will walk you through setting up a project that writes some
-simple matrix math functions. Please put this portion in a folder marked Part2
-in your repository. 
-
-### Step 1 : Create your project.
-Using the instructions on the Google forum, please set up a new Visual Studio project that
-compiles using CUDA. For uniformity, please write your main function and all
-your code in a file named matrix_math.cu.
-
-### Step 2 : Setting up CUDA memory.
-As we discussed in class, there is host memory and device memory.  Host memory
-is the memory that exists on the CPU, whereas device memory is memory on the
-GPU.  
-
-In order to create/reserve memory on the GPU, we need to explicitly do so
-using cudaMalloc.  By calling cudaMalloc, we are calling malloc on the GPU to
-reserve a portion of its memory.  Like malloc, cudaMalloc simply mallocs a
-portion of memory and returns a pointer. This memory is only accessible on the
-device unless we explicitly copy memory from the GPU to the CPU.  The reverse is
-also true.  
-
-We can copy memory to and from the GPU using the function cudaMemcpy. Like the
-POSIX C memcpy, you will need to specify the size of memory you are copying.
-The last argument is used to specify the direction of the copy (from GPU to CPU
-or the other way around).
-
-Please initialize 2 5 x 5 matrices represented as an array of floats on the CPU
-and the GPU where each of the entry is equal to its position (i.e. A_00 = 0,
-A_01 = 1, A_44 = 24). 
-
-### Step 3 : Creating CUDA kernels. 
-In the previous part, we explicitly divided the CUDA kernels from the rest of
-the file for stylistic purposes.  Since there will be far less code in this
-project, we will write the global and device functions in the same file as the
-main function.
-
-Given a matrix A and matrix B (both represented as arrays of floats), please
-write the following functions :
-* mat_add : A + B
-* mat_sub : A - B
-* mat_mult : A * B
-
-You may assume for all matrices that the dimensions of A and B are the same and
-that they are square.
-
-Use the 2 5 x 5 matrices to test your code either by printing directly to the
-console or writing an assert.
-
-THINGS TO REMEMBER :
-* global and device functions only have access to memory that is explicitly on
-  the device, meaning you MUST copy memory from the CPU to the GPU if you would
-  like to use it there
-* The triple triangle braces "<<<" begin and end the global function call.  This
-  provides parameters with which CUDA uses to set up tile size, block size and
-  threads for each warp.
-* Do not fret if Intellisense does not understand CUDA keywords (if they have
-  red squiggly lines underneath CUDA keywords).  There is a way to integrate
-  CUDA syntax highlighting into Visual Studio, but it is not the default.
-
-### Step 4 : Write a serial version.
-For comparison, write a single-threaded CPU version of mat_add, mat_sub and
-mat_mult. We will not introduce timing elements in this project, but please
-keep them in mind as the upcoming lab will introduce more on this topic. 
-
-## PART 4 : PERFORMANCE ANALYSIS
-Since this is the first project, we will guide you with some example
-questions.  In future projects, please answer at least these questions, as
-they go through basic performance analysis.  Please go above and beyond the
-questions we suggest and explore how different aspects of your code impact
-performance as a whole. 
-
-We have provided a frame counter as a metric, but feel free to add cudaTimers,
-etc. to do more fine-grained benchmarking of various aspects. 
-
-NOTE : Performance should be measured in comparison to a baseline.  Be sure to
-describe the changes you make between experiments and how you are benchmarking.
-
-* How does changing the tile and block sizes change performance? Why?
-* How does changing the number of planets change performance? Why?
-* Without running experiments, how would you expect the serial and GPU verions
-  of matrix_math to compare?  Why?
-
-## SUBMISSION
-Please commit your changes to your forked version of the repository and open a
-pull request.  Please write your performance analysis in your README.md.
-Remember to email Harmony (harmoli+CIS565@seas.upenn.edu) your grade and why.
+Performance Analysis
+
+1. Changing the tile/block sizes
+	Comparing the differences between block sizes of powers of two indicates that there is an
+	optimal size (128) and going up or down decreases the performance.  Increasing the block
+	size should allow more threads to share memory and decrease the downtime from loading the
+	data, but reduces the number of memory fetches that can be performed at once?  I'm not sure.
+
+2. Changing the number of planets
+	Increasing the number of planets decreases performance, while decreasing the number of
+	planets increases performance.  There are a few causes for this.  First of all, increasing
+	the number of planets increases the number of calculations per thread (by a linear factor).
+	Second, the number of threads increases (also by a linear factor) because more planets need
+	to be processed (I don't know if I have the terms right here).
+
+3. Comparing serial/GPU versions of matrix math
+	The GPU version should take far, far less time than the serial version for large matrices.
+	With the 5x5 array that we have, the difference is small.  However, the GPU version's add
+	and subtract should scale linearly with the width, while a serial calculation scales with
+	width^2.  The multiply should scale both by another factor of the width.
+
+4. Improving the performance of nbody by not using glm
+	I noticed while writing the nbody simulation code that glm::normalize() was significantly
+	reducing the performance.  I had 3 calls to the method, and it took my down to 2fps.
+	With a manual version (vector/width), I got 30 fps instead.  In addition, replacing my
+	calls to glm::length() with sqrt(x^2+y^2+z^2) improved it to 60 fps.  My guess is that
+	it is simply faster to do things locally if possible, since it doesn't need to use
+	external code.
\ No newline at end of file
diff --git a/README_instructions.md b/README_instructions.md
new file mode 100644
index 0000000..70ae0d3
--- /dev/null
+++ b/README_instructions.md
@@ -0,0 +1,120 @@
+Project 1
+=========
+
+# Project 1 : Introduction to CUDA
+
+## NOTE :
+This project (and all other projects in this course) requires a NVIDIA graphics
+card with CUDA capabilityi!  Any card with compute capability 2.0 and up will
+work.  This means any card from the GeForce 400 and 500 series and afterwards
+will work.  If you do not have a machine with these specs, feel free to use
+computers in the SIG Lab.  All computers in SIG lab and Moore 100 C have CUDA 
+capable cards and should already have the CUDA SDK installed. 
+
+## PART 1 : INSTALL NSIGHT
+To help with benchmarking and performance analysis, we will be using NVIDIA's
+profiling and debugging tool named NSight. Download and install it from the
+following link for whichever IDE you will be using:
+http://www.nvidia.com/object/nsight.html. 
+
+NOTE : If you are using Linux / Mac, most of the screenshots and class usage of
+NSight will be in Visual Studio.  You are free to use to the Eclipse version
+NSight during these in class labs, but we will not be able to help you as much.
+
+## PART 2 : NBODY SIMULATION
+To get you used to using CUDA kernels, we will be writing a simple 2D nbody 
+simulator.  The following source files are included in the project:
+
+* main.cpp : sets up graphics stuff for visualization
+* kernel.cu : this contains the CUDA kernel calls
+
+All the code that you will need to modify is in kernel.cu and is marked clearly
+by TODOs.
+
+## PART 3 : MATRIX MATH
+In this portion we will walk you through setting up a project that writes some
+simple matrix math functions. Please put this portion in a folder marked Part2
+in your repository. 
+
+### Step 1 : Create your project.
+Using the instructions on the Google forum, please set up a new Visual Studio project that
+compiles using CUDA. For uniformity, please write your main function and all
+your code in a file named matrix_math.cu.
+
+### Step 2 : Setting up CUDA memory.
+As we discussed in class, there is host memory and device memory.  Host memory
+is the memory that exists on the CPU, whereas device memory is memory on the
+GPU.  
+
+In order to create/reserve memory on the GPU, we need to explicitly do so
+using cudaMalloc.  By calling cudaMalloc, we are calling malloc on the GPU to
+reserve a portion of its memory.  Like malloc, cudaMalloc simply mallocs a
+portion of memory and returns a pointer. This memory is only accessible on the
+device unless we explicitly copy memory from the GPU to the CPU.  The reverse is
+also true.  
+
+We can copy memory to and from the GPU using the function cudaMemcpy. Like the
+POSIX C memcpy, you will need to specify the size of memory you are copying.
+The last argument is used to specify the direction of the copy (from GPU to CPU
+or the other way around).
+
+Please initialize 2 5 x 5 matrices represented as an array of floats on the CPU
+and the GPU where each of the entry is equal to its position (i.e. A_00 = 0,
+A_01 = 1, A_44 = 24). 
+
+### Step 3 : Creating CUDA kernels. 
+In the previous part, we explicitly divided the CUDA kernels from the rest of
+the file for stylistic purposes.  Since there will be far less code in this
+project, we will write the global and device functions in the same file as the
+main function.
+
+Given a matrix A and matrix B (both represented as arrays of floats), please
+write the following functions :
+* mat_add : A + B
+* mat_sub : A - B
+* mat_mult : A * B
+
+You may assume for all matrices that the dimensions of A and B are the same and
+that they are square.
+
+Use the 2 5 x 5 matrices to test your code either by printing directly to the
+console or writing an assert.
+
+THINGS TO REMEMBER :
+* global and device functions only have access to memory that is explicitly on
+  the device, meaning you MUST copy memory from the CPU to the GPU if you would
+  like to use it there
+* The triple triangle braces "<<<" begin and end the global function call.  This
+  provides parameters with which CUDA uses to set up tile size, block size and
+  threads for each warp.
+* Do not fret if Intellisense does not understand CUDA keywords (if they have
+  red squiggly lines underneath CUDA keywords).  There is a way to integrate
+  CUDA syntax highlighting into Visual Studio, but it is not the default.
+
+### Step 4 : Write a serial version.
+For comparison, write a single-threaded CPU version of mat_add, mat_sub and
+mat_mult. We will not introduce timing elements in this project, but please
+keep them in mind as the upcoming lab will introduce more on this topic. 
+
+## PART 4 : PERFORMANCE ANALYSIS
+Since this is the first project, we will guide you with some example
+questions.  In future projects, please answer at least these questions, as
+they go through basic performance analysis.  Please go above and beyond the
+questions we suggest and explore how different aspects of your code impact
+performance as a whole. 
+
+We have provided a frame counter as a metric, but feel free to add cudaTimers,
+etc. to do more fine-grained benchmarking of various aspects. 
+
+NOTE : Performance should be measured in comparison to a baseline.  Be sure to
+describe the changes you make between experiments and how you are benchmarking.
+
+* How does changing the tile and block sizes change performance? Why?
+* How does changing the number of planets change performance? Why?
+* Without running experiments, how would you expect the serial and GPU verions
+  of matrix_math to compare?  Why?
+
+## SUBMISSION
+Please commit your changes to your forked version of the repository and open a
+pull request.  Please write your performance analysis in your README.md.
+Remember to email Harmony (harmoli+CIS565@seas.upenn.edu) your grade and why.