def softmax(x): # x[ M, K] e_x = exp(x - max(x, axis=1)) # 这里首先对K个元素进行 return e_x / e_x.sum(axis=1) 这里的减法和除法都是元素操作(elementwise operation),对于多线程并行计算的时候,让每一个元素都执行相同的操作就可以。 此外这里还有求取最大值和求和的规约操作(reductio...
比如以下代码示例: // Sets bit in output[] to 1 if the correspond element in data[i] // is greater than ‘threshold’, using 32 threads in a warp. for(int i=warpLane; i<dataLen; i+=warpSize) { unsigned active = __activemask(); unsigned bitPack = __ballot_sync(active, data[i...
) = cuInit(0)# Get attributeserr, DEVICE_NAME = cuDeviceGetName(128, 0)DEVICE_NAME = DEVICE_NAME.decode("ascii").replace("\x00", "")err, MAX_THREADS_PER_BLOCK = cuDeviceGetAttribute( CUdevice_attribute.
__device__ float GetElement(const Matrix A, int row, int col) { return A.elements[row * A.stride + col]; } // Set a matrix element __device__ void SetElement(Matrix A, int row, int col, float value) { A.elements[row * A.stride + col] = value; } // Get the BLOCK_SIZE...
T* pElement = (T*)((char*)BaseAddress + Row * pitch) + Column; For allocations of 2D arrays, it is recommended that programmers consider performing pitch allocations using cudaMallocPitch(). Due to pitch alignment restrictions in the hardware, this is especially true if the application...
性能够高,应用这套 Elementwise 模板的算子都能打满机器的带宽,速度也够快。 开发效率高,开发人员可以不用过分关注 CUDA 逻辑及相关优化手段,只需要编写计算逻辑即可。 可扩展性强,目前这套模板支持了一元,二元,三元操作。若今后有需求拓展,支持更多输入时,只需要仿照编写对应的工厂即可。
LDSM Load Matrix from Shared Memory with Element Size Expansion STSM Store Matrix to Shared Memory ST Store to Generic Memory STG Store to Global Memory STL Store to Local Memory STS Store to Shared Memory STAS Asynchronous Store to Distributed Shared Memory With Explicit Synchronization SYNCS Sync...
(); // 2、分配主机内存和设备内存,并初始化 int ielement = 513; // 设置元素个数 size_t stBytescount = ielement * sizeof(float); // 字节数 // 分配主机内存,并初始化 float *fphost_a,*fphost_b,*fphost_c; fphost_a = (float*)malloc(stBytescount); fphost_b = (float*)malloc(...
We recently updated our oldthrust::tupleimplementation to be an alias forcuda::std::tuple. Unfortunately, when providing the necessary backfills forthrust::tuple_sizeto work withthrust::null_typesomeone (me) missed to add the final overload for a 10 element tuple. My apologies for the disrupt...
GPU加速应用程序与CPU应用程序对比:在CPU应用程序中,数据在CPU上分配,并且所有工作均在CPU上执行,而在加速应用程序中,则可使用cudaMallocManaged()分配数据,其数据可由CPU进行访问和处理,并能自动迁移至可执行并行工作的GPU,GPU异步执行工作,与此同时CPU可执行它的工作,通过cudaDeviceSynchronize(), CPU代码可与异步GP...