zheng-da commented on a change in pull request #9947: [WIP] Performance
optimization for dot(csr, rsp) on cpu
URL: https://github.com/apache/incubator-mxnet/pull/9947#discussion_r173386908
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File path: src/operator/tensor/dot-inl.h
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@@ -793,16 +764,21 @@ inline void DotCsrRspDnsImpl(const OpContext& ctx,
mxnet_op::Kernel<mxnet_op::set_zero, cpu>::Launch(s, num_threads,
ret->dptr<DType>());
}
- num_threads = mxnet_op::get_num_threads<cpu>(ret->shape_[0]);
- dim_t seg_len = (ret->shape_[0] + num_threads - 1) / num_threads;
+ num_threads = ret->shape_[0];
if (trans_lhs) {
LOG(FATAL) << "DotCsrRspDnsImpl has not implemented dot(csr.T,
rsp) = dns yet";
} else {
+ const RType* row_idx_ptr = row_idx_r.dptr<RType>();
+ std::unordered_map<RType, dim_t> row_idx_map;
+ row_idx_map.reserve(nnr * 7);
+ for (dim_t ind = 0; ind < nnr; ind++) {
+ row_idx_map.emplace(row_idx_ptr[ind], ind);
+ }
Review comment:
@eric-haibin-lin if we maintain an array for mapping and an array for
recording the number of non-zero entries in the mapping array, the overhead of
cleaning the mapping is O(nnr).
@reminisce depending on how we use a tree to store the index. we can achieve
O(log_k N) accesses. in practice, k is a large number (e.g., 128), so it's 3 or
4 memory accesses before finding the right location. memory overhead is
O(min(N, k * nnr)). it might be better than using a single array or hashtable.
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