InfiniTensor/include/utils/small_array.h

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tensor parallel for transformer (#125) * add cmake bits about NCCL * move example to examples/NNmodel * impl NCCL communicator * add comm related function to Runtime * export runtime interface * add launch.py * use unique name to distingush the the NCCL ID file * add timeout to communicator init * expose communicator obj from runtime obj, add unit test for nccl communicator * reformat files * Add allReduce operator and cuda nccl allReduce kernel * impl model parallel for resnet * add allGather nccl kernel and operator * Add allreduce allgather operator tests, change allgather kernel to output list of tensor, fix shape infer, handle nullptr output * fix format of onnx.py * use concat following AllGather * get tensor parallel for resnet * fix format of graph_handler.cc * change BUILD_DIST default to OFF * polish code of communicator * update .gitignore * export min/max to python * fix MatMul * modify launch.py to run opt * hack to treat ReduceSum as AllReduceSum * throw exception in cuda error * fix parallel_opt.py * improve the error prompt and cuda error check * fix GatherObj::GatherObj member init * fix size calculation for scalar (rank = 0) tensor * MatMul supports bias * fix add bias for row parallel gemm * add --gen_std to launch.py * fix AllReduceNCCL * update launch.py * less log * update parallel_opt * update launch.py * add __eq__ for Placement sub-classes * less benchmark run * fix placement infer for matmul * fix vacabuary size * fix Exception * Add shard tensor with group to support gpt2 * Add find successor function to find split op at different depth * recover CommunicatorObj * improve error mesasge * optimize parallel_opt.py * optimize launch.py * recover docs for all_reduce and all_gather * Fix API * fix format --------- Co-authored-by: panzezhong <panzezhong@qiyuanlab.com> Co-authored-by: Haojie Wang <haojie0429@gmail.com>
2023-09-14 14:19:45 +08:00
#pragma once
namespace infini {
#define SMALL_ARRAY_SIZE 8
struct SmallArray {
int data[SMALL_ARRAY_SIZE];
int prod(int start, int end) {
int result = 1;
for (int i = start; i < end; ++i) {
result *= data[i];
}
return result;
}
};
} // namespace infini