Hi, recently I try to use NCCL_MAX_NCHANNELS = 10 to limit nccl:all_to_all operation grid_size(SM counts) from torch/distributed/distributed_c10d.py(3881): all_to_all_single, but result shows that grid_size is 16, which is still larger than 10. So is it a problem with the usage...
int* rings) { // Gather data from all ranks int *ringRecv, *ringSend, *ringPrev, *ringNext, *treeUpRecv, *treeUpSend, *treeDnRecv,*treeDnSend; int nranks = comm->nRanks; int nChannels = comm->nChannels; NCCLCHECK(ncclCalloc(&ringRecv, nranks*MAXCHANNELS...
I want to dynamically set nccl_max_nchannels in the program. hope allreduce uses different SM numbers under different conditions, is there any way to achieve this?Activity gcongiu commented on Jan 9, 2025 gcongiu on Jan 9, 2025 You can use ncclCommInitRankConfig and set maxCTAs in nccl...
struct ncclTopoGraph { // Input / output int id; // ring : 0, tree : 1, collnet : 2 int pattern; int crossNic; int collNet; int minChannels; int maxChannels; // Output int nChannels; // 搜索到的channel数量 float speedIntra; // 节点内单个channel带宽 float...
nChannels = comm->nChannels = std::min((int)ncclMaxNchannels(), nChannels); int c; for (c=nChannels; c<ncclMinNchannels(); c++) { memcpy(ringPrev+c*nranks, ringPrev+(c-nChannels)*nranks, nranks*sizeof(int)); memcpy(ringNext+c*nranks, ringNext+(c-nChannels)*nranks, nranks*...
00/16: 第00个通道,16表示通道总数 (nChannels),数字标志rank的顺序。 通道中rank之间的收发信息连接的设备打印日志: NCCL INFO Channel 00 : 8[5b000] -> 0[5b000] [send] via NET/IB/0/GDRDMANCCL INFO Channel 01 : 8[5b000] -> 0[5b000] [send] via NET/IB/1/GDRDMA ...
static ncclResult_t connectRings(struct ncclComm* comm, int* ringRecv, int* ringSend, int* ringPrev, int* ringNext, int* firstRanks) { int nChannels = comm->nChannels; int nNodes = comm->nNodes; for (int c=0; c<nChannels; c++) { int* recv = ringRecv+c*comm->nRanks; int* ...
NCCL_MAX_NCHANNELS¶ (NCCL_MAX_NRINGS since 2.0.5, NCCL_MAX_NCHANNELS since 2.5.0) TheNCCL_MAX_NCHANNELSvariable limits the number of channels NCCL can use. Reducing the number of channels also reduces the number of CUDA blocks used for communication, hence the impact on GPU computing reso...
NCCL_MAX_NCHANNELS¶ (NCCL_MAX_NRINGS since 2.0.5, NCCL_MAX_NCHANNELS since 2.5.0) TheNCCL_MAX_NCHANNELSvariable limits the number of channels NCCL can use. Reducing the number of channels also reduces the number of CUDA blocks used for communication, hence the impact on GPU computing reso...
比如: nn.Conv2d 需要一个4D Tensor, 形状为(nSamples, nChannels, Height, Width). 如果你的输入只有单一样本形式, 则需要执行input.unsqueeze(0), 主动将3D Tensor扩充成4D Tensor. 损失函数 损失函数的输入是一个输入的pair: (output, target), 然后计算出一个数值来评估output和target之间的差距大小. ...