/external/XNNPACK/test/ |
D | qs8-gemm-minmax.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_qs8_gemm_minmax_ukernel_2x8c8__aarch64_neon_mlal_padal 6 k-block: 16 7 - name: xnn_qs8_gemm_minmax_ukernel_2x8c8__aarch64_neon_mull_padal 8 k-block: 8 9 - name: xnn_qs8_gemm_minmax_ukernel_1x8__neon_mlal_lane 10 k-block: 8 11 - name: xnn_qs8_gemm_minmax_ukernel_2x8__neon_mlal_lane 12 k-block: 8 13 - name: xnn_qs8_gemm_minmax_ukernel_4x8__neon_mlal_lane [all …]
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D | f32-gemm-minmax.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_f32_gemm_minmax_ukernel_1x8__aarch64_neonfma_ld64 6 k-block: 2 8 - name: xnn_f32_gemm_minmax_ukernel_1x8__aarch64_neonfma_cortex_a53 9 k-block: 8 12 - name: xnn_f32_gemm_minmax_ukernel_1x8__aarch64_neonfma_cortex_a57 13 k-block: 8 16 - name: xnn_f32_gemm_minmax_ukernel_1x8__aarch64_neonfma_cortex_a75 17 k-block: 8 20 - name: xnn_f32_gemm_minmax_ukernel_4x8__aarch64_neonfma_cortex_a53 [all …]
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D | qs8-igemm-minmax.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_qs8_igemm_minmax_ukernel_2x8c8__aarch64_neon_mlal_padal 6 k-block: 16 7 - name: xnn_qs8_igemm_minmax_ukernel_2x8c16__aarch64_neon_mlal_padal 8 k-block: 16 9 - name: xnn_qs8_igemm_minmax_ukernel_1x8__neon_mlal_lane 10 k-block: 8 11 - name: xnn_qs8_igemm_minmax_ukernel_2x8__neon_mlal_lane 12 k-block: 8 13 - name: xnn_qs8_igemm_minmax_ukernel_4x8__neon_mlal_lane [all …]
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D | f32-igemm-minmax.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_f32_igemm_minmax_ukernel_1x8__aarch64_neonfma_cortex_a53 6 k-block: 8 9 - name: xnn_f32_igemm_minmax_ukernel_1x8__aarch64_neonfma_cortex_a57 10 k-block: 8 13 - name: xnn_f32_igemm_minmax_ukernel_1x8__aarch64_neonfma_cortex_a75 14 k-block: 8 17 - name: xnn_f32_igemm_minmax_ukernel_4x8__aarch64_neonfma_cortex_a53 18 k-block: 4 21 - name: xnn_f32_igemm_minmax_ukernel_4x8__aarch64_neonfma_cortex_a55 [all …]
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D | f32-gemminc-minmax.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_f32_gemminc_minmax_ukernel_1x8__aarch64_neonfma_cortex_a53 6 k-block: 8 9 - name: xnn_f32_gemminc_minmax_ukernel_1x8__aarch64_neonfma_cortex_a57 10 k-block: 8 13 - name: xnn_f32_gemminc_minmax_ukernel_1x8__aarch64_neonfma_cortex_a75 14 k-block: 8 17 - name: xnn_f32_gemminc_minmax_ukernel_4x8__aarch64_neonfma_cortex_a53 18 k-block: 4 21 - name: xnn_f32_gemminc_minmax_ukernel_4x8__aarch64_neonfma_cortex_a55 [all …]
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D | f32-spmm-minmax.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_f32_spmm_minmax_ukernel_4x1__neon 6 k-block: 1 7 - name: xnn_f32_spmm_minmax_ukernel_4x1__neon_pipelined 8 k-block: 1 9 - name: xnn_f32_spmm_minmax_ukernel_4x1__neon_x2 10 k-block: 2 11 - name: xnn_f32_spmm_minmax_ukernel_8x1__neon 12 k-block: 1 13 - name: xnn_f32_spmm_minmax_ukernel_8x1__neon_pipelined [all …]
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D | f16-gemm-minmax.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_f16_gemm_minmax_ukernel_1x8__neonfp16arith_ld64 6 k-block: 4 8 - aarch64 9 - name: xnn_f16_gemm_minmax_ukernel_4x8__neonfp16arith_ld64 10 k-block: 4 12 - aarch64 13 - name: xnn_f16_gemm_minmax_ukernel_6x8__neonfp16arith_ld64 14 k-block: 4 16 - aarch64 [all …]
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D | f32-gemm.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_f32_gemm_ukernel_4x4__aarch32_vfp_ld64 6 k-block: 2 8 - name: xnn_f32_gemm_ukernel_1x8__wasmsimd_splat 9 k-block: 4 10 - name: xnn_f32_gemm_ukernel_4x8__wasmsimd_splat 11 k-block: 4 12 - name: xnn_f32_gemm_ukernel_5x8__wasmsimd_splat 13 k-block: 4 14 - name: xnn_f32_gemm_ukernel_4x2c4__wasmsimd [all …]
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D | f32-gemm-relu.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_f32_gemm_relu_ukernel_1x8__wasmsimd_splat 6 k-block: 4 7 - name: xnn_f32_gemm_relu_ukernel_4x8__wasmsimd_splat 8 k-block: 4 9 - name: xnn_f32_gemm_relu_ukernel_5x8__wasmsimd_splat 10 k-block: 4 11 - name: xnn_f32_gemm_relu_ukernel_4x2c4__wasmsimd 12 k-block: 4 13 - name: xnn_f32_gemm_relu_ukernel_1x4__wasm [all …]
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D | f32-igemm.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_f32_igemm_ukernel_1x8__wasmsimd_splat 6 k-block: 4 7 - name: xnn_f32_igemm_ukernel_4x8__wasmsimd_splat 8 k-block: 4 9 - name: xnn_f32_igemm_ukernel_5x8__wasmsimd_splat 10 k-block: 4 11 - name: xnn_f32_igemm_ukernel_4x2c4__wasmsimd 12 k-block: 4 13 - name: xnn_f32_igemm_ukernel_1x4__wasm [all …]
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D | f32-igemm-relu.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_f32_igemm_relu_ukernel_1x8__wasmsimd_splat 6 k-block: 4 7 - name: xnn_f32_igemm_relu_ukernel_4x8__wasmsimd_splat 8 k-block: 4 9 - name: xnn_f32_igemm_relu_ukernel_5x8__wasmsimd_splat 10 k-block: 4 11 - name: xnn_f32_igemm_relu_ukernel_4x2c4__wasmsimd 12 k-block: 4 13 - name: xnn_f32_igemm_relu_ukernel_1x4__wasm [all …]
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D | f32-ppmm-minmax.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_f32_ppmm_minmax_ukernel_4x8__neon 6 k-block: 1 7 - name: xnn_f32_ppmm_minmax_ukernel_4x8__neonfma 8 k-block: 1 9 - name: xnn_f32_ppmm_minmax_ukernel_8x8__neon 10 k-block: 1 11 - name: xnn_f32_ppmm_minmax_ukernel_8x8__neonfma 12 k-block: 1 13 - name: xnn_f32_ppmm_minmax_ukernel_4x8__sse [all …]
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D | f16-igemm-minmax.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_f16_igemm_minmax_ukernel_1x8__neonfp16arith_ld64 6 k-block: 4 8 - aarch64 9 - name: xnn_f16_igemm_minmax_ukernel_4x8__neonfp16arith_ld64 10 k-block: 4 12 - aarch64 13 - name: xnn_f16_igemm_minmax_ukernel_6x8__neonfp16arith_ld64 14 k-block: 4 16 - aarch64 [all …]
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D | f16-spmm-minmax.yaml | 3 # This source code is licensed under the BSD-style license found in the 5 - name: xnn_f16_spmm_minmax_ukernel_8x1__neonfp16arith 6 k-block: 1 8 - aarch64 9 - name: xnn_f16_spmm_minmax_ukernel_8x1__neonfp16arith_x2 10 k-block: 2 12 - aarch64 13 - name: xnn_f16_spmm_minmax_ukernel_16x1__neonfp16arith 14 k-block: 1 16 - aarch64 [all …]
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/external/bzip2/ |
D | bzip2.1 | 4 bzip2, bunzip2 \- a block-sorting file compressor, v1.0.6 6 bzcat \- decompresses files to stdout 8 bzip2recover \- recovers data from damaged bzip2 files 13 .RB [ " \-cdfkqstvzVL123456789 " ] 20 .RB [ " \-fkvsVL " ] 26 .RB [ " \-s " ] 36 compresses files using the Burrows-Wheeler block sorting 39 LZ77/LZ78-based compressors, and approaches the performance of the PPM 42 The command-line options are deliberately very similar to 49 command-line flags. Each file is replaced by a compressed version of [all …]
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D | bzip2.txt | 3 bzip2, bunzip2 - a block-sorting file compressor, v1.0.6 4 bzcat - decompresses files to stdout 5 bzip2recover - recovers data from damaged bzip2 files 9 bzip2 [ -cdfkqstvzVL123456789 ] [ filenames ... ] 10 bunzip2 [ -fkvsVL ] [ filenames ... ] 11 bzcat [ -s ] [ filenames ... ] 16 bzip2 compresses files using the Burrows-Wheeler block 19 achieved by more conventional LZ77/LZ78-based compressors, 20 and approaches the performance of the PPM family of sta- 23 The command-line options are deliberately very similar to [all …]
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D | blocksort.c | 2 /*-------------------------------------------------------------*/ 3 /*--- Block sorting machinery ---*/ 4 /*--- blocksort.c ---*/ 5 /*-------------------------------------------------------------*/ 7 /* ------------------------------------------------------------------ 9 lossless, block-sorting data compression. 12 Copyright (C) 1996-2010 Julian Seward <jseward@bzip.org> 19 ------------------------------------------------------------------ */ 24 /*---------------------------------------------*/ 25 /*--- Fallback O(N log(N)^2) sorting ---*/ [all …]
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/external/mesa3d/src/gallium/drivers/llvmpipe/ |
D | lp_rast_debug.c | 67 const struct cmd_block *block, in get_variant() argument 68 int k ) in get_variant() argument 73 if (block->cmd[k] == LP_RAST_OP_SHADE_TILE || in get_variant() 74 block->cmd[k] == LP_RAST_OP_SHADE_TILE_OPAQUE || in get_variant() 75 block->cmd[k] == LP_RAST_OP_TRIANGLE_1 || in get_variant() 76 block->cmd[k] == LP_RAST_OP_TRIANGLE_2 || in get_variant() 77 block->cmd[k] == LP_RAST_OP_TRIANGLE_3 || in get_variant() 78 block->cmd[k] == LP_RAST_OP_TRIANGLE_4 || in get_variant() 79 block->cmd[k] == LP_RAST_OP_TRIANGLE_5 || in get_variant() 80 block->cmd[k] == LP_RAST_OP_TRIANGLE_6 || in get_variant() [all …]
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/external/tensorflow/tensorflow/core/kernels/ |
D | eigen_spatial_convolutions.h | 7 http://www.apache.org/licenses/LICENSE-2.0 23 #include "tensorflow/core/kernels/eigen_spatial_convolutions-inl.h" 36 EIGEN_ALWAYS_INLINE static Index finalize(Scalar* block, 40 const Index num_coeffs = max_depth - depth; 44 *block = pad ? Scalar(0) : rhs.coeffNoPadding(depth, base_idx); 45 ++block; 55 EIGEN_ALWAYS_INLINE static Index finalize(Scalar* block, 59 Index num_coeffs = max_depth - depth; 66 internal::pstoreu(block, p, mask<Packet>(0, num_coeffs)); 72 // Pack a block of the right input matrix (in our case it's always a [all …]
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/external/libjpeg-turbo/simd/x86_64/ |
D | jcphuff-sse2.asm | 2 ; jcphuff-sse2.asm - prepare data for progressive Huffman encoding 3 ; (64-bit SSE2) 8 ; Copyright (C) 1999-2006, MIYASAKA Masaru. 22 ; -------------------------------------------------------------------------- 26 ; -------------------------------------------------------------------------- 36 pinsrw X0, word [BLOCK + T0 * 2], 0 37 pinsrw X1, word [BLOCK + T1 * 2], 0 41 pinsrw X0, word [BLOCK + T0 * 2], 1 42 pinsrw X1, word [BLOCK + T1 * 2], 1 46 pinsrw X0, word [BLOCK + T0 * 2], 2 [all …]
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/external/tensorflow/tensorflow/core/kernels/linalg/ |
D | cholesky_grad.cc | 7 http://www.apache.org/licenses/LICENSE-2.0 64 MatrixMap output_matrix = outputs->at(0); in ComputeMatrix() 76 block_end -= kMaxBlockSize) { in ComputeMatrix() 77 /* This shows the block structure. in ComputeMatrix() 87 const int64 block_begin = std::max(int64{0}, block_end - kMaxBlockSize); in ComputeMatrix() 88 const int64 block_size = block_end - block_begin; in ComputeMatrix() 89 const int64 trailing_size = kMatrixSize - block_end; in ComputeMatrix() 91 auto B = input_matrix_l.block(block_end, 0, trailing_size, block_begin); in ComputeMatrix() 93 output_matrix.block(block_end, 0, trailing_size, block_begin); in ComputeMatrix() 95 auto C = input_matrix_l.block(block_end, block_begin, trailing_size, in ComputeMatrix() [all …]
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/external/libjpeg-turbo/simd/i386/ |
D | jcphuff-sse2.asm | 2 ; jcphuff-sse2.asm - prepare data for progressive Huffman encoding (SSE2) 7 ; Copyright (C) 1999-2006, MIYASAKA Masaru. 21 ; -------------------------------------------------------------------------- 25 ; -------------------------------------------------------------------------- 35 pinsrw X0, word [BLOCK + T0 * 2], 0 36 pinsrw X1, word [BLOCK + T1 * 2], 0 40 pinsrw X0, word [BLOCK + T0 * 2], 1 41 pinsrw X1, word [BLOCK + T1 * 2], 1 45 pinsrw X0, word [BLOCK + T0 * 2], 2 46 pinsrw X1, word [BLOCK + T1 * 2], 2 [all …]
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/external/apache-commons-math/src/main/java/org/apache/commons/math/linear/ |
D | BlockFieldMatrix.java | 9 * http://www.apache.org/licenses/LICENSE-2.0 30 * Cache-friendly implementation of FieldMatrix using a flat arrays to store 33 * This implementation is specially designed to be cache-friendly. Square blocks are 35 * and columns major direction, one block at a time. This greatly increases performances 52 * As an example, for a block size of 36x36, a 100x60 matrix would be stored in 6 blocks. 53 * Block 0 would be a Field[1296] array holding the upper left 36x36 square, block 1 would be 54 * a Field[1296] array holding the upper center 36x36 square, block 2 would be a Field[1008] 55 * array holding the upper right 36x28 rectangle, block 3 would be a Field[864] array holding 56 * the lower left 24x36 rectangle, block 4 would be a Field[864] array holding the lower center 57 * 24x36 rectangle and block 5 would be a Field[672] array holding the lower right 24x28 [all …]
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D | BlockRealMatrix.java | 9 * http://www.apache.org/licenses/LICENSE-2.0 29 * Cache-friendly implementation of RealMatrix using a flat arrays to store 32 * This implementation is specially designed to be cache-friendly. Square blocks are 34 * and columns major direction, one block at a time. This greatly increases performances 42 * for processors with 64k L1 cache (one block holds 2704 values or 21632 bytes). This value 43 * could be lowered to 36x36 for processors with 32k L1 cache. 53 * As an example, for a block size of 52x52, a 100x60 matrix would be stored in 4 blocks. 54 * Block 0 would be a double[2704] array holding the upper left 52x52 square, block 1 would be 55 * a double[416] array holding the upper right 52x8 rectangle, block 2 would be a double[2496] 56 * array holding the lower left 48x52 rectangle and block 3 would be a double[384] array [all …]
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/external/eigen/Eigen/src/SVD/ |
D | UpperBidiagonalization.h | 5 // Copyright (C) 2013-2014 Gael Guennebaud <gael.guennebaud@inria.fr> 80 .setLength(m_householder.cols()-1) in householderV() 111 for (Index k = 0; /* breaks at k==cols-1 below */ ; ++k) variable 113 Index remainingRows = rows - k; 114 Index remainingCols = cols - k - 1; 116 // construct left householder transform in-place in A 117 mat.col(k).tail(remainingRows) 118 .makeHouseholderInPlace(mat.coeffRef(k,k), diagonal[k]); 121 .applyHouseholderOnTheLeft(mat.col(k).tail(remainingRows-1), mat.coeff(k,k), tempData); 123 if(k == cols-1) break; [all …]
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