我正在阅读CUDA5.0示例(AdvancedQuickSort)。但是,由于以下代码,我无法完全理解此示例:
// Now compute my own personal offset within this. I need to know how many
// threads with a lane ID less than mine are going to write to the same buffer
// as me. We can use popc to implement a single-operation warp scan in this case.
unsigned
我尝试使用下面的Makefile从编译代码。这是一个GPU燃烧器使用CUDA和我的Mac确实有GT750M。
1 CUDAPATH=/usr/local/cuda
2
3 # Have this point to an old enough gcc (for nvcc)
4 GCCPATH=/usr/bin/clang
5
6 NVCC=nvcc
7 CCPATH=${GCCPATH}/bin
8
9 drv:
10 PATH=${PATH}:.:${CCPATH}:${PATH} ${NVCC} -I${CUDAPATH}/include
我使用内联PTX ld.shared从共享内存加载数据:
__shared__ float As[BLOCK_SIZE][BLOCK_SIZE]; //declare a buffer in shared memory
float Csub = 0;
As[TY][TX] = A[a + wA * TY + TX]; //load data from global memory to shared memory
__syncthreads();
float t;
asm("ld.shared.f32 %0, [%1];" :"=f"(
我正在尝试使用共享内存来缓存OpenACC。
基本上,我所做的是矩阵乘法,我有:
typedef float ff;
// Multiplies two square row-major matrices a and b, puts the result in c.
void mmul(const restrict ff* a,
const restrict ff* b,
restrict ff* c,
const int n) {
#pragma acc data copyin(a[0:n*n], b[0:n*n])
我目前正在尝试使用tensorflow 2.4.0自定义训练神经网络,使用RTX 3070运行CUDA 11.0和CUDNN 8。
我遇到了这样一个问题,我可以训练模型,但实际上无法获得任何输出,因为当我运行时:
output = model(x)遇到以下消息,我的jupyter内核会自动重新启动。
2021-01-08 20:52:53.437668: W tensorflow/stream_executor/gpu/asm_compiler.cc:191] Falling back to the CUDA driver for PTX compilation; ptxas does not