mirror of
https://github.com/fatedier/frp.git
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185 lines
5.8 KiB
Go
185 lines
5.8 KiB
Go
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//+build !noasm
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//+build !appengine
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//+build !gccgo
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// Copyright 2015, Klaus Post, see LICENSE for details.
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// Copyright 2019, Minio, Inc.
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package reedsolomon
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//go:noescape
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func _galMulAVX512Parallel82(in, out [][]byte, matrix *[matrixSize82]byte, addTo bool)
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//go:noescape
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func _galMulAVX512Parallel84(in, out [][]byte, matrix *[matrixSize84]byte, addTo bool)
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const (
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dimIn = 8 // Number of input rows processed simultaneously
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dimOut82 = 2 // Number of output rows processed simultaneously for x2 routine
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dimOut84 = 4 // Number of output rows processed simultaneously for x4 routine
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matrixSize82 = (16 + 16) * dimIn * dimOut82 // Dimension of slice of matrix coefficient passed into x2 routine
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matrixSize84 = (16 + 16) * dimIn * dimOut84 // Dimension of slice of matrix coefficient passed into x4 routine
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)
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// Construct block of matrix coefficients for 2 outputs rows in parallel
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func setupMatrix82(matrixRows [][]byte, inputOffset, outputOffset int, matrix *[matrixSize82]byte) {
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offset := 0
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for c := inputOffset; c < inputOffset+dimIn; c++ {
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for iRow := outputOffset; iRow < outputOffset+dimOut82; iRow++ {
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if c < len(matrixRows[iRow]) {
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coeff := matrixRows[iRow][c]
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copy(matrix[offset*32:], mulTableLow[coeff][:])
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copy(matrix[offset*32+16:], mulTableHigh[coeff][:])
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} else {
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// coefficients not used for this input shard (so null out)
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v := matrix[offset*32 : offset*32+32]
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for i := range v {
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v[i] = 0
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}
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}
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offset += dimIn
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if offset >= dimIn*dimOut82 {
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offset -= dimIn*dimOut82 - 1
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}
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}
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}
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}
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// Construct block of matrix coefficients for 4 outputs rows in parallel
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func setupMatrix84(matrixRows [][]byte, inputOffset, outputOffset int, matrix *[matrixSize84]byte) {
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offset := 0
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for c := inputOffset; c < inputOffset+dimIn; c++ {
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for iRow := outputOffset; iRow < outputOffset+dimOut84; iRow++ {
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if c < len(matrixRows[iRow]) {
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coeff := matrixRows[iRow][c]
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copy(matrix[offset*32:], mulTableLow[coeff][:])
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copy(matrix[offset*32+16:], mulTableHigh[coeff][:])
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} else {
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// coefficients not used for this input shard (so null out)
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v := matrix[offset*32 : offset*32+32]
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for i := range v {
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v[i] = 0
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}
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}
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offset += dimIn
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if offset >= dimIn*dimOut84 {
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offset -= dimIn*dimOut84 - 1
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}
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}
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}
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}
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// Invoke AVX512 routine for 2 output rows in parallel
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func galMulAVX512Parallel82(in, out [][]byte, matrixRows [][]byte, inputOffset, outputOffset int) {
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done := len(in[0])
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if done == 0 {
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return
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}
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inputEnd := inputOffset + dimIn
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if inputEnd > len(in) {
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inputEnd = len(in)
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}
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outputEnd := outputOffset + dimOut82
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if outputEnd > len(out) {
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outputEnd = len(out)
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}
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matrix82 := [matrixSize82]byte{}
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setupMatrix82(matrixRows, inputOffset, outputOffset, &matrix82)
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addTo := inputOffset != 0 // Except for the first input column, add to previous results
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_galMulAVX512Parallel82(in[inputOffset:inputEnd], out[outputOffset:outputEnd], &matrix82, addTo)
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done = (done >> 6) << 6
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if len(in[0])-done == 0 {
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return
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}
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for c := inputOffset; c < inputOffset+dimIn; c++ {
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for iRow := outputOffset; iRow < outputOffset+dimOut82; iRow++ {
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if c < len(matrixRows[iRow]) {
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mt := mulTable[matrixRows[iRow][c]][:256]
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for i := done; i < len(in[0]); i++ {
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if c == 0 { // only set value for first input column
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out[iRow][i] = mt[in[c][i]]
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} else { // and add for all others
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out[iRow][i] ^= mt[in[c][i]]
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}
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}
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}
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}
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}
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}
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// Invoke AVX512 routine for 4 output rows in parallel
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func galMulAVX512Parallel84(in, out [][]byte, matrixRows [][]byte, inputOffset, outputOffset int) {
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done := len(in[0])
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if done == 0 {
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return
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}
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inputEnd := inputOffset + dimIn
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if inputEnd > len(in) {
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inputEnd = len(in)
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}
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outputEnd := outputOffset + dimOut84
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if outputEnd > len(out) {
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outputEnd = len(out)
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}
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matrix84 := [matrixSize84]byte{}
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setupMatrix84(matrixRows, inputOffset, outputOffset, &matrix84)
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addTo := inputOffset != 0 // Except for the first input column, add to previous results
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_galMulAVX512Parallel84(in[inputOffset:inputEnd], out[outputOffset:outputEnd], &matrix84, addTo)
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done = (done >> 6) << 6
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if len(in[0])-done == 0 {
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return
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}
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for c := inputOffset; c < inputOffset+dimIn; c++ {
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for iRow := outputOffset; iRow < outputOffset+dimOut84; iRow++ {
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if c < len(matrixRows[iRow]) {
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mt := mulTable[matrixRows[iRow][c]][:256]
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for i := done; i < len(in[0]); i++ {
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if c == 0 { // only set value for first input column
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out[iRow][i] = mt[in[c][i]]
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} else { // and add for all others
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out[iRow][i] ^= mt[in[c][i]]
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}
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}
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}
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}
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}
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}
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// Perform the same as codeSomeShards, but taking advantage of
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// AVX512 parallelism for up to 4x faster execution as compared to AVX2
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func (r reedSolomon) codeSomeShardsAvx512(matrixRows, inputs, outputs [][]byte, outputCount, byteCount int) {
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outputRow := 0
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// First process (multiple) batches of 4 output rows in parallel
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for ; outputRow+dimOut84 <= len(outputs); outputRow += dimOut84 {
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for inputRow := 0; inputRow < len(inputs); inputRow += dimIn {
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galMulAVX512Parallel84(inputs, outputs, matrixRows, inputRow, outputRow)
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}
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}
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// Then process a (single) batch of 2 output rows in parallel
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if outputRow+dimOut82 <= len(outputs) {
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// fmt.Println(outputRow, len(outputs))
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for inputRow := 0; inputRow < len(inputs); inputRow += dimIn {
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galMulAVX512Parallel82(inputs, outputs, matrixRows, inputRow, outputRow)
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}
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outputRow += dimOut82
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}
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// Lastly, we may have a single output row left (for uneven parity)
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if outputRow < len(outputs) {
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for c := 0; c < r.DataShards; c++ {
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if c == 0 {
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galMulSlice(matrixRows[outputRow][c], inputs[c], outputs[outputRow], &r.o)
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} else {
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galMulSliceXor(matrixRows[outputRow][c], inputs[c], outputs[outputRow], &r.o)
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}
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}
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}
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}
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