Add files of initial version

CMakeLists.txt

+CMAKE_MINIMUM_REQUIRED(VERSION 2.6)
+    PROJECT( BioEM )
+    
+    FIND_PACKAGE(CUDA)
+
+    SET( CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O3 -march=native -fopenmp -fweb -mfpmath=sse -frename-registers -minline-all-stringops -ftracer -funroll-loops -fpeel-loops -fprefetch-loop-arrays -ffast-math -ggdb" )
+    
+    SET( CUDA_NVCC_FLAGS "${CUDA_NVCC_FLAGS};-gencode arch=compute_35,code=sm_35;--use_fast_math;-ftz=true;-O4;-Xptxas -O4" )
+
+    INCLUDE_DIRECTORIES( include  $HOME/usr/include )
+
+    CUDA_ADD_EXECUTABLE( bioEM bioem.cpp  main.cpp  map.cpp  model.cpp  param.cpp cmodules/timer.cpp bioem_cuda.cu )
+    
+    SET( CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++0x -Wall -Wno-vla -Wno-unused-result -pedantic" )
+
+    TARGET_LINK_LIBRARIES( bioEM -lfftw3 -fopenmp -lboost_program_options )
+
+   
\ No newline at end of file

README

+********************************************************
+    BioEM:  Bayesian inference of Electron Microscopy
+********************************************************
+
+Requisites: 
+
+	**** FFTW libraries:   http://www.fftw.org/
+
+        **** BOOST libraries:  http://www.boost.org/
+
+        **** OpenMP:           http://openmp.org/
+
+Optional: 
+        **** CMake:            http://www.cmake.org/
+	     for compliation with CMakeLists.txt file.
+  
+**********************************************************

bioem_algorithm.h

+#ifndef BIOEM_ALGORITHM_H
+#define BIOEM_ALGORITHM_H
+
+template <int GPUAlgo, class RefT>
+__device__ static inline void compareRefMap(const int iRefMap, const int iOrient, const int iConv, const bioem_map& Mapconv, bioem_Probability* pProb, const bioem_param_device& param, const RefT& RefMap,
+	const int cent_x, const int cent_y, const int myShift = 0, const int nShifts2 = 0, const int myRef = 0)
+{
+    /**************************************************************************************/
+    /**********************  Calculating BioEM Probability ********************************/
+    /************************* Loop of center displacement here ***************************/
+
+    // Taking into account the center displacement
+
+    /*** Inizialzing crosscorrelations of calculated projected convolutions ***/
+    myfloat_t sum=0.0;
+    myfloat_t sumsquare=0.0;
+    myfloat_t crossproMapConv=0.0;
+
+    /****** Loop over Pixels to calculate dot product and cross-correlations of displaced Ref Conv. Map***/
+	if (GPUAlgo != 2 || iRefMap < RefMap.ntotRefMap) 
+	{
+		int iStart, jStart, iEnd, jEnd;
+		if (cent_x < 0)
+		{
+			iStart = -cent_x;
+			iEnd = param.NumberPixels;
+		}
+		else
+		{
+			iStart = 0;
+			iEnd = param.NumberPixels - cent_x;
+		}
+		if (cent_y < 0)
+		{
+			jStart = -cent_y;
+			jEnd = param.NumberPixels;
+		}
+		else
+		{
+			jStart = 0;
+			jEnd = param.NumberPixels - cent_y;
+		}
+
+		for (int i = iStart; i < iEnd; i += 1)
+		{
+			for (int j = jStart; j < jEnd; j += 1)
+			{
+				const myfloat_t pointMap = Mapconv.points[i+cent_x][j+cent_y];
+				const myfloat_t pointRefMap = RefMap.get(iRefMap, i, j);
+				crossproMapConv += pointMap * pointRefMap;
+				// Crosscorrelation of calculated displaced map
+				sum += pointMap;
+				// Calculate Sum of pixels squared
+				sumsquare += pointMap*pointMap;
+			}
+		}
+	}
+	
+    /********** Calculating elements in BioEM Probability formula ********/
+    // Related to Reference calculated Projection
+    const myfloat_t ForLogProb = (sumsquare * param.Ntotpi - sum * sum);
+
+    // Products of different cross-correlations (first element in formula)
+    const myfloat_t firstele = param.Ntotpi * (RefMap.sumsquare_RefMap[iRefMap] * sumsquare-crossproMapConv * crossproMapConv) +
+                             2 * RefMap.sum_RefMap[iRefMap] * sum * crossproMapConv - RefMap.sumsquare_RefMap[iRefMap] * sum * sum - RefMap.sum_RefMap[iRefMap] * RefMap.sum_RefMap[iRefMap] * sumsquare;
+
+    //******* Calculating log of Prob*********/
+    // As in fortran code: logpro=(3-Ntotpi)*0.5*log(firstele/pConvMap[iOrient].ForLogProbfromConv[iConv])+(Ntotpi*0.5-2)*log(Ntotpi-2)-0.5*log(pConvMap[iOrient].ForLogProbfromConv[iConv])+0.5*log(PI)+(1-Ntotpi*0.5)*(log(2*PI)+1);
+    const myfloat_t logpro = (3 - param.Ntotpi) * 0.5 * log(firstele) + (param.Ntotpi * 0.5 - 2) * log((param.Ntotpi - 2) * ForLogProb);
+
+#ifdef BIOEM_GPUCODE
+	if (GPUAlgo == 2)
+	{
+		extern __shared__ myfloat_t buf[];
+		myfloat_t* buf2 = &buf[myBlockDimX];
+		myfloat_t* buf3 = &buf2[myBlockDimX + 4 * myRef];
+		int* bufint = (int*) buf3;
+		
+		buf[myThreadIdxX] = logpro;
+		if (myShift == 0)
+		{
+			bufint[0] = 0;
+		}
+		__syncthreads();
+		
+		if (nShifts2 == CUDA_MAX_SHIFT_REDUCE) // 1024
+		{
+			if (myShift < 512) if (buf[myThreadIdxX + 512] > buf[myThreadIdxX]) buf[myThreadIdxX] = buf[myThreadIdxX + 512];
+			__syncthreads();
+		}
+		
+		if (nShifts2 >= 512)
+		{
+			if (myShift < 256) if (buf[myThreadIdxX + 256] > buf[myThreadIdxX]) buf[myThreadIdxX] = buf[myThreadIdxX + 256];
+			__syncthreads();
+		}
+
+		if (nShifts2 >= 256)
+		{
+			if (myShift < 128) if (buf[myThreadIdxX + 128] > buf[myThreadIdxX]) buf[myThreadIdxX] = buf[myThreadIdxX + 128];
+			__syncthreads();
+		}
+
+		if (nShifts2 >= 128)
+		{
+			if (myShift < 64) if (buf[myThreadIdxX + 64] > buf[myThreadIdxX]) buf[myThreadIdxX] = buf[myThreadIdxX + 64];
+			__syncthreads();
+		}
+
+		if (myShift < 32) //Warp Size is 32, threads are synched automatically
+		{
+			volatile float* vbuf = buf; //Mem must be volatile such that memory access is not reordered
+			if (nShifts2 >= 64 && vbuf[myThreadIdxX + 32] > vbuf[myThreadIdxX]) vbuf[myThreadIdxX] = vbuf[myThreadIdxX + 32];
+			if (nShifts2 >= 32 && vbuf[myThreadIdxX + 16] > vbuf[myThreadIdxX]) vbuf[myThreadIdxX] = vbuf[myThreadIdxX + 16];
+			if (nShifts2 >= 16 && vbuf[myThreadIdxX + 8] > vbuf[myThreadIdxX]) vbuf[myThreadIdxX] = vbuf[myThreadIdxX + 8];
+			if (nShifts2 >= 8 && vbuf[myThreadIdxX + 4] > vbuf[myThreadIdxX]) vbuf[myThreadIdxX] = vbuf[myThreadIdxX + 4];
+			if (nShifts2 >= 4 && vbuf[myThreadIdxX + 2] > vbuf[myThreadIdxX]) vbuf[myThreadIdxX] = vbuf[myThreadIdxX + 2];
+			if (nShifts2 >= 2 && vbuf[myThreadIdxX + 1] > vbuf[myThreadIdxX]) vbuf[myThreadIdxX] = vbuf[myThreadIdxX + 1];
+			if (myShift == 0 && iRefMap < RefMap.ntotRefMap)
+			{
+				const myfloat_t logpro_max = vbuf[myThreadIdxX];
+				if(pProb[iRefMap].Constoadd < logpro_max)
+				{
+					pProb[iRefMap].Total = pProb[iRefMap].Total * exp(-logpro_max + pProb[iRefMap].Constoadd);
+					pProb[iRefMap].Constoadd = logpro_max;
+				}
+				if(pProb[iRefMap].ConstAngle[iOrient] < logpro_max)
+				{
+					pProb[iRefMap].forAngles[iOrient] = pProb[iRefMap].forAngles[iOrient] * exp(-logpro_max + pProb[iRefMap].ConstAngle[iOrient]);
+					pProb[iRefMap].ConstAngle[iOrient] = logpro_max;
+				}
+				if(pProb[iRefMap].max_prob < logpro_max)
+				{
+					pProb[iRefMap].max_prob = logpro_max;
+					pProb[iRefMap].max_prob_orient = iOrient;
+					pProb[iRefMap].max_prob_conv = iConv;
+					bufint[0] = 1;
+					buf3[1] = logpro_max;
+				}
+			}
+		}
+		
+		__syncthreads();
+		if (bufint[0] == 1 && buf3[1] == logpro && iRefMap < RefMap.ntotRefMap && atomicAdd(&bufint[0], 1) == 1)
+		{
+			pProb[iRefMap].max_prob_cent_x = cent_x;
+			pProb[iRefMap].max_prob_cent_y = cent_y;
+		}
+		
+		__syncthreads();
+		
+		if (iRefMap < RefMap.ntotRefMap)
+		{
+			buf[myThreadIdxX] = exp(logpro - pProb[iRefMap].Constoadd);
+			buf2[myThreadIdxX] = exp(logpro - pProb[iRefMap].ConstAngle[iOrient]);
+		}
+		__syncthreads();
+		
+		if (nShifts2 == CUDA_MAX_SHIFT_REDUCE) // 1024
+		{
+			if (myShift < 512)
+			{
+				buf[myThreadIdxX] += buf[myThreadIdxX + 512];
+				buf2[myThreadIdxX] += buf2[myThreadIdxX + 512];
+			}
+			__syncthreads();
+		}
+		
+		if (nShifts2 >= 512)
+		{
+			if (myShift < 256)
+			{
+				buf[myThreadIdxX] += buf[myThreadIdxX + 256];
+				buf2[myThreadIdxX] += buf2[myThreadIdxX + 256];
+			}
+			__syncthreads();
+		}
+
+		if (nShifts2 >= 256)
+		{
+			if (myShift < 128)
+			{
+				buf[myThreadIdxX] += buf[myThreadIdxX + 128];
+				buf2[myThreadIdxX] += buf2[myThreadIdxX + 128];
+			}
+			__syncthreads();
+		}
+
+		if (nShifts2 >= 128)
+		{
+			if (myShift < 64)
+			{
+				buf[myThreadIdxX] += buf[myThreadIdxX + 64];
+				buf2[myThreadIdxX] += buf2[myThreadIdxX + 64];
+			}
+			__syncthreads();
+		}
+
+		if (myShift < 32) //Warp Size is 32, threads are synched automatically
+		{
+			volatile float* vbuf = buf; //Mem must be volatile such that memory access is not reordered
+			volatile float* vbuf2 = buf2;
+			if (nShifts2 >= 64)
+			{
+				vbuf[myThreadIdxX] += vbuf[myThreadIdxX + 32];
+				vbuf2[myThreadIdxX] += vbuf2[myThreadIdxX + 32];
+			}
+			if (nShifts2 >= 32)
+			{
+				vbuf[myThreadIdxX] += vbuf[myThreadIdxX + 16];
+				vbuf2[myThreadIdxX] += vbuf2[myThreadIdxX + 16];
+			}
+			if (nShifts2 >= 16)
+			{
+				vbuf[myThreadIdxX] += vbuf[myThreadIdxX + 8];
+				vbuf2[myThreadIdxX] += vbuf2[myThreadIdxX + 8];
+			}
+			if (nShifts2 >= 8)
+			{
+				vbuf[myThreadIdxX] += vbuf[myThreadIdxX + 4];
+				vbuf2[myThreadIdxX] += vbuf2[myThreadIdxX + 4];
+			}
+			if (nShifts2 >= 4)
+			{
+				vbuf[myThreadIdxX] += vbuf[myThreadIdxX + 2];
+				vbuf2[myThreadIdxX] += vbuf2[myThreadIdxX + 2];
+			}
+			if (nShifts2 >= 2)
+			{
+				vbuf[myThreadIdxX] += vbuf[myThreadIdxX + 1];
+				vbuf2[myThreadIdxX] += vbuf2[myThreadIdxX + 1];
+			}
+			if (myShift == 0 && iRefMap < RefMap.ntotRefMap)
+			{
+				pProb[iRefMap].Total += vbuf[myThreadIdxX];
+				pProb[iRefMap].forAngles[iOrient] += vbuf2[myThreadIdxX];
+			}
+		}
+	}
+	else
+#endif
+
+    /***** Summing & Storing total/Orientation Probabilites for each map ************/
+    {
+        /*******  Summing total Probabilities *************/
+        /******* Need a constant because of numerical divergence*****/
+        if(pProb[iRefMap].Constoadd < logpro)
+        {
+            pProb[iRefMap].Total = pProb[iRefMap].Total * exp(-logpro + pProb[iRefMap].Constoadd);
+            pProb[iRefMap].Constoadd = logpro;
+        }
+        pProb[iRefMap].Total += exp(logpro - pProb[iRefMap].Constoadd);
+
+		//Summing probabilities for each orientation
+        if(pProb[iRefMap].ConstAngle[iOrient] < logpro)
+        {
+            pProb[iRefMap].forAngles[iOrient] = pProb[iRefMap].forAngles[iOrient] * exp(-logpro + pProb[iRefMap].ConstAngle[iOrient]);
+            pProb[iRefMap].ConstAngle[iOrient] = logpro;
+		}
+        pProb[iRefMap].forAngles[iOrient] += exp(logpro - pProb[iRefMap].ConstAngle[iOrient]);
+
+        /********** Getting parameters that maximize the probability ***********/
+        if(pProb[iRefMap].max_prob < logpro)
+        {
+            pProb[iRefMap].max_prob = logpro;
+            pProb[iRefMap].max_prob_cent_x = cent_x;
+            pProb[iRefMap].max_prob_cent_y = cent_y;
+            pProb[iRefMap].max_prob_orient = iOrient;
+            pProb[iRefMap].max_prob_conv = iConv;
+        }
+    }
+}
+
+template <int GPUAlgo, class RefT>
+__device__ static inline void compareRefMapShifted(const int iRefMap, const int iOrient, const int iConv, const bioem_map& Mapconv, bioem_Probability* pProb, const bioem_param_device& param, const RefT& RefMap)
+{
+    for (int cent_x = -param.maxDisplaceCenter; cent_x <= param.maxDisplaceCenter; cent_x=cent_x+param.GridSpaceCenter)
+    {
+        for (int cent_y = -param.maxDisplaceCenter; cent_y <= param.maxDisplaceCenter; cent_y=cent_y+param.GridSpaceCenter)
+        {
+			compareRefMap<GPUAlgo>(iRefMap, iOrient, iConv, Mapconv, pProb, param, RefMap, cent_x, cent_y);
+        }
+    }
+}
+
+#endif

bioem_cuda.cu

+#define BIOEM_GPUCODE
+
+#if defined(_WIN32)
+#include <windows.h>
+#endif
+
+#include <iostream>
+using namespace std;
+
+#include "bioem_cuda_internal.h"
+#include "bioem_algorithm.h"
+
+//__constant__ bioem_map gConvMap;
+
+static inline void checkCudaErrors(cudaError_t error)
+{
+	if (error != cudaSuccess)
+	{
+		printf("CUDA Error %d / %s\n", error, cudaGetErrorString(error));
+		exit(1);
+	}
+}
+
+bioem_cuda::bioem_cuda()
+{
+	deviceInitialized = 0;
+	GPUAlgo = getenv("GPUALGO") == NULL ? 2 : atoi(getenv("GPUALGO"));
+}
+
+bioem_cuda::~bioem_cuda()
+{
+	deviceExit();
+}
+
+__global__ void compareRefMap_kernel(const int iOrient, const int iConv, const bioem_map* pMap, bioem_Probability* pProb, const bioem_param_device param, const bioem_RefMap_Mod* RefMap, const int cent_x, const int cent_y)
+{
+	const int iRefMap = myBlockIdxX * myBlockDimX + myThreadIdxX;
+	if (iRefMap < RefMap->ntotRefMap)
+	{
+		compareRefMap<0>(iRefMap,iOrient,iConv,*pMap, pProb, param, *RefMap, cent_x, cent_y);
+	}
+}
+
+__global__ void compareRefMapShifted_kernel(const int iOrient, const int iConv, const bioem_map* pMap, bioem_Probability* pProb, const bioem_param_device param, const bioem_RefMap_Mod* RefMap)
+{
+	const int iRefMap = myBlockIdxX * myBlockDimX + myThreadIdxX;
+	if (iRefMap < RefMap->ntotRefMap)
+	{
+		compareRefMapShifted<1>(iRefMap,iOrient,iConv,*pMap, pProb, param, *RefMap);
+	}
+}
+
+__global__ void compareRefMapLoopShifts_kernel(const int iOrient, const int iConv, const bioem_map* pMap, bioem_Probability* pProb, const bioem_param_device param, const bioem_RefMap* RefMap, const int blockoffset, const int nShifts, const int nShiftBits)
+{
+	const size_t myid = (myBlockIdxX + blockoffset) * myBlockDimX + myThreadIdxX;
+	const int iRefMap = myid >> (nShiftBits << 1);
+	const int myRef = myThreadIdxX >> (nShiftBits << 1);
+	const int myShiftIdx = (myid >> nShiftBits) & (nShifts - 1);
+	const int myShiftIdy = myid & (nShifts - 1);
+	const int myShift = myid & (nShifts * nShifts - 1);
+	const int cent_x = myShiftIdx * param.GridSpaceCenter - param.maxDisplaceCenter;
+	const int cent_y = myShiftIdy * param.GridSpaceCenter - param.maxDisplaceCenter;
+	
+	compareRefMap<2>(iRefMap,iOrient,iConv,*pMap, pProb, param, *RefMap, cent_x, cent_y, myShift, nShifts * nShifts, myRef);
+}
+
+template <class T> static inline T divup(T num, T divider) {return((num + divider - 1) / divider);}
+static inline bool IsPowerOf2(int x) {return ((x > 0) && ((x & (x - 1)) == 0));}
+#if defined(_WIN32)
+static inline int ilog2 (int value)
+{
+	DWORD index;
+	_BitScanReverse (&index, value);
+	return(value);
+}
+#else
+static inline int ilog2(int value) {return 31 - __builtin_clz(value);}
+#endif
+
+int bioem_cuda::compareRefMaps(int iProjectionOut, int iConv, const bioem_map& conv_map)
+{
+	//cudaMemcpyToSymbolAsync(&gConvMap, &conv_map, sizeof(bioem_map), 0, cudaMemcpyHostToDevice, cudaStream);
+	checkCudaErrors(cudaMemcpyAsync(pConvMap_device, &conv_map, sizeof(bioem_map), cudaMemcpyHostToDevice, cudaStream));
+	
+	if (GPUAlgo == 2) //Loop over shifts
+	{
+		const int nShifts = 2 * param.param_device.maxDisplaceCenter / param.param_device.GridSpaceCenter + 1;
+		if (!IsPowerOf2(nShifts))
+		{
+			cout << "Invalid number of displacements, no power of two\n";
+			exit(1);
+		}
+		if (CUDA_THREAD_COUNT % (nShifts * nShifts))
+		{
+			cout << "CUDA Thread count is no multiple of number of shifts\n";
+			exit(1);
+		}
+		if (nShifts > CUDA_MAX_SHIFT_REDUCE)
+		{
+			cout << "Too many displacements for CUDA reduction\n";
+			exit(1);
+		}
+		const int nShiftBits = ilog2(nShifts);
+		size_t totalBlocks = divup((size_t) RefMap.ntotRefMap * (size_t) nShifts * (size_t) nShifts, (size_t) CUDA_THREAD_COUNT);
+		size_t nBlocks = CUDA_BLOCK_COUNT;
+		for (size_t i = 0;i < totalBlocks;i += nBlocks)
+		{
+			compareRefMapLoopShifts_kernel <<<min(nBlocks, totalBlocks - i), CUDA_THREAD_COUNT, (CUDA_THREAD_COUNT * 2 + CUDA_THREAD_COUNT / (nShifts * nShifts) * 4) * sizeof(myfloat_t), cudaStream>>> (iProjectionOut, iConv, pConvMap_device, pProb_device, param.param_device, pRefMap_device, i, nShifts, nShiftBits);
+		}
+	}
+	else if (GPUAlgo == 1) //Split shifts in multiple kernels
+	{
+		for (int cent_x = -param.param_device.maxDisplaceCenter; cent_x <= param.param_device.maxDisplaceCenter; cent_x=cent_x+param.param_device.GridSpaceCenter)
+		{
+			for (int cent_y = -param.param_device.maxDisplaceCenter; cent_y <= param.param_device.maxDisplaceCenter; cent_y=cent_y+param.param_device.GridSpaceCenter)
+			{
+				compareRefMap_kernel <<<divup(RefMap.ntotRefMap, CUDA_THREAD_COUNT), CUDA_THREAD_COUNT, 0, cudaStream>>> (iProjectionOut, iConv, pConvMap_device, pProb_device, param.param_device, pRefMap_device_Mod, cent_x, cent_y);
+			}
+		}	
+	}
+	else if (GPUAlgo == 0) //All shifts in one kernel
+	{
+		compareRefMapShifted_kernel <<<divup(RefMap.ntotRefMap, CUDA_THREAD_COUNT), CUDA_THREAD_COUNT, 0, cudaStream>>> (iProjectionOut, iConv, pConvMap_device, pProb_device, param.param_device, pRefMap_device_Mod);
+	}
+	else
+	{
+		cout << "Invalid GPU Algorithm selected\n";
+		exit(1);
+	}
+	checkCudaErrors(cudaStreamSynchronize(cudaStream));
+	return(0);
+}
+
+int bioem_cuda::deviceInit()
+{
+	deviceExit();
+	
+	checkCudaErrors(cudaStreamCreate(&cudaStream));
+	checkCudaErrors(cudaMalloc(&pRefMap_device, sizeof(bioem_RefMap)));
+	checkCudaErrors(cudaMalloc(&pProb_device, sizeof(bioem_Probability) * RefMap.ntotRefMap));
+	checkCudaErrors(cudaMalloc(&pConvMap_device, sizeof(bioem_map)));
+	pRefMap_device_Mod = (bioem_RefMap_Mod*) pRefMap_device;
+	
+	if (GPUAlgo == 0 || GPUAlgo == 1)
+	{
+		bioem_RefMap_Mod* RefMapGPU = new bioem_RefMap_Mod(RefMap);
+		cudaMemcpy(pRefMap_device_Mod, RefMapGPU, sizeof(bioem_RefMap), cudaMemcpyHostToDevice);
+		delete RefMapGPU;
+	}
+	else
+	{
+		cudaMemcpy(pRefMap_device, &RefMap, sizeof(bioem_RefMap), cudaMemcpyHostToDevice);
+	}
+	deviceInitialized = 1;
+	return(0);
+}
+
+int bioem_cuda::deviceExit()
+{
+	if (deviceInitialized == 0) return(0);
+	
+	cudaStreamDestroy(cudaStream);
+	cudaFree(pRefMap_device);
+	cudaFree(pProb_device);
+	cudaFree(pConvMap_device);
+	cudaThreadExit();
+	
+	deviceInitialized = 0;
+	return(0);
+}
+
+int bioem_cuda::deviceStartRun()
+{
+	
+	cudaMemcpy(pProb_device, pProb, sizeof(bioem_Probability) * RefMap.ntotRefMap, cudaMemcpyHostToDevice);
+	return(0);
+}
+
+int bioem_cuda::deviceFinishRun()
+{
+	cudaMemcpy(pProb, pProb_device, sizeof(bioem_Probability) * RefMap.ntotRefMap, cudaMemcpyDeviceToHost);
+	
+	return(0);
+}
+
+bioem* bioem_cuda_create()
+{
+	return new bioem_cuda;
+}

cmodules/affinity.cpp

+#ifdef _WIN32
+#include "pthread_mutex_win32_wrapper.h"
+#else
+#include <sys/types.h>
+#include <sys/syscall.h>
+#include <syscall.h>
+#include <dirent.h>
+#include <pthread.h>
+#endif
+#include <vector>
+#include "affinity.h"
+#include <string>
+#include <stdio.h>
+#include <stdlib.h>
+#include "os_low_level_helper.h"
+
+#ifndef STD_OUT
+#define STD_OUT stdout
+#endif
+
+pid_t gettid()
+{
+#ifdef _WIN32
+	return((pid_t) GetCurrentThreadId());
+#else
+	return((pid_t) syscall(SYS_gettid));
+#endif
+}
+
+#ifdef _WIN32
+pid_t getpid()
+{
+	return((pid_t) GetCurrentProcessId());
+}
+#endif
+
+struct threadNameStruct
+{
+	pid_t thread_id;
+	std::string name;
+};
+
+class lockClass
+{
+public:
+    lockClass() {pthread_mutex_init(&lock, NULL);}
+    ~lockClass() {pthread_mutex_destroy(&lock);}
+    std::vector<threadNameStruct> threadNames;
+    pthread_mutex_t lock;
+};
+
+static lockClass lockedVector;
+
+void setThreadName(char* name)
+{
+	threadNameStruct tmp;
+	tmp.thread_id = gettid();
+	tmp.name = name;
+	pthread_mutex_lock(&lockedVector.lock);
+	lockedVector.threadNames.push_back(tmp);
+	pthread_mutex_unlock(&lockedVector.lock);
+}
+
+void setUnknownNames(char* name)
+{
+	pid_t pid = getpid();
+#ifndef _WIN32
+	char dirname[1024];
+	sprintf(dirname, "/proc/%d/task", (int) pid);
+	DIR* dp = opendir(dirname);
+	if (dp)
+	{
+		dirent* ent;
+		while ((ent = readdir(dp)) != NULL)
+		{
+			pid_t tid = atoi(ent->d_name);
+			if (tid != 0 && tid != pid)
+			{
+				int found = false;
+				for (size_t i = 0;i < lockedVector.threadNames.size();i++)
+				{
+					if (lockedVector.threadNames[i].thread_id == tid)
+					{
+						found = true;