ANIKET SHIVAM
co-authored by
Aniket Shivam
Aniket Shivam
parent
ca23ff7924
commit
b72cbf957d
@@ -684,6 +684,154 @@ struct TestbedConv2dProblemSizes {
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};
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////////////////////////////////////////////////////////////////////////////
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/// Structure TestbedGroupConv2dProblemSizes initializes and holds group conv default and
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/// important network sizes
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////////////////////////////////////////////////////////////////////////////
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struct TestbedGroupConv2dProblemSizes {
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//
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// Data members
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//
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int threadblock_n;
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int threadblock_k;
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int minimum_channel_size;
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Conv2dProblemVector default_single_group_sizes;
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Conv2dProblemVector default_multiple_group_sizes;
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//
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// Methods
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//
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/// Default ctor
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TestbedGroupConv2dProblemSizes(
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int threadblock_n_,
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int threadblock_k_,
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int minimum_channel_size_ = 64)
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: threadblock_n (threadblock_n_),
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threadblock_k (threadblock_k_),
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minimum_channel_size (minimum_channel_size_) {
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initialize_group_conv2d_default_sizes();
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filter_all();
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}
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/// Eliminates some illegal cases
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void filter_all() {
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Conv2dProblemVector *problems_vectors[] = {
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&default_single_group_sizes,
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&default_multiple_group_sizes
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};
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for (Conv2dProblemVector *problems : problems_vectors) {
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Conv2dProblemVector filtered;
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for (cutlass::conv::Conv2dProblemSize const & problem : *problems) {
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if (!((problem.C / problem.groups) % minimum_channel_size)) {
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filtered.push_back(problem);
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}
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}
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*problems = filtered;
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}
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}
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// Add a few standard convolution problem sizes
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void initialize_group_conv2d_default_sizes() {
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////////////////////////////////////////////////////////////////////////////////////
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// One group calculated by one or multiple CTAs: k_per_group % CTA::N = 0
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// One CTA calculates a single group
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////////////////////////////////////////////////////////////////////////////////////
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for (int cta_per_group_k = 1; cta_per_group_k < 4; ++cta_per_group_k) {
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// groups = 2, 3, 4
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for (int groups = 2; groups < 5; ++groups) {
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int conv_k = cta_per_group_k * threadblock_n * groups;
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default_single_group_sizes.push_back(cutlass::conv::Conv2dProblemSize(
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{1, 8, 8, threadblock_k * 2 * groups}, // input size (NHWC)
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{conv_k, 3, 3, threadblock_k * 2}, // filter size (KRSC)
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{1, 1, 1, 1}, // padding (pad_h, _, pad_w, _)
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{1, 1}, // stride (stride_h, stride_w)
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{1, 1}, // dilation (dilation_h, dilation_w)
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cutlass::conv::Mode::kCrossCorrelation,
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1, // split_k_slices
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groups // groups
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));
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} // loop groups
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} // loop cta_per_group_k
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// Partial gemm_k: k_per_group == CTA::N && channels_per_group < CTA::K
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default_single_group_sizes.push_back(cutlass::conv::Conv2dProblemSize(
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{1, 8, 8, threadblock_k}, // input size (NHWC)
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{threadblock_n * 2, 3, 3, threadblock_k / 2}, // filter size (KRSC)
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{1, 1, 1, 1}, // padding (pad_h, _, pad_w, _)
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{1, 1}, // stride (stride_h, stride_w)
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{1, 1}, // dilation (dilation_h, dilation_w)
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cutlass::conv::Mode::kCrossCorrelation,
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1, // split_k_slices
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2 // groups
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));
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////////////////////////////////////////////////////////////////////////////////////
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// One CTA calculate multiple groups: CTA::N % k_per_group = 0
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////////////////////////////////////////////////////////////////////////////////////
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// 2 groups per CTA
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default_multiple_group_sizes.push_back(cutlass::conv::Conv2dProblemSize(
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{1, 8, 8, threadblock_k * 4}, // input size (NHWC)
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{threadblock_n, 3, 3, threadblock_k * 2}, // filter size (KRSC)
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{1, 1, 1, 1}, // padding (pad_h, _, pad_w, _)
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{1, 1}, // stride (stride_h, stride_w)
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{1, 1}, // dilation (dilation_h, dilation_w)
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cutlass::conv::Mode::kCrossCorrelation,
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1, // split_k_slices
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2 // groups
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));
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// 2 groups per CTA and partial gemm_k
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default_multiple_group_sizes.push_back(cutlass::conv::Conv2dProblemSize(
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{1, 8, 8, threadblock_k}, // input size (NHWC)
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{threadblock_n, 3, 3, threadblock_k / 2}, // filter size (KRSC)
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{1, 1, 1, 1}, // padding (pad_h, _, pad_w, _)
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{1, 1}, // stride (stride_h, stride_w)
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{1, 1}, // dilation (dilation_h, dilation_w)
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cutlass::conv::Mode::kCrossCorrelation,
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1, // split_k_slices
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2 // groups
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));
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// 4 groups per CTA
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default_multiple_group_sizes.push_back(cutlass::conv::Conv2dProblemSize(
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{1, 8, 8, threadblock_k * 8}, // input size (NHWC)
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{threadblock_n / 2, 3, 3, threadblock_k * 2}, // filter size (KRSC)
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{1, 1, 1, 1}, // padding (pad_h, _, pad_w, _)
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{1, 1}, // stride (stride_h, stride_w)
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{1, 1}, // dilation (dilation_h, dilation_w)
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cutlass::conv::Mode::kCrossCorrelation,
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1, // split_k_slices
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4 // groups
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));
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// 4 groups per CTA and partial gemm_k
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default_multiple_group_sizes.push_back(cutlass::conv::Conv2dProblemSize(
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{1, 8, 8, threadblock_k * 2}, // input size (NHWC)
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{threadblock_n / 2, 3, 3, threadblock_k / 2}, // filter size (KRSC)
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{1, 1, 1, 1}, // padding (pad_h, _, pad_w, _)
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{1, 1}, // stride (stride_h, stride_w)
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{1, 1}, // dilation (dilation_h, dilation_w)
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cutlass::conv::Mode::kCrossCorrelation,
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1, // split_k_slices
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4 // groups
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));
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}
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};
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} // namespace device
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} // namespace conv
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} // namespace test
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