296 lines
9.7 KiB
Plaintext
296 lines
9.7 KiB
Plaintext
/*
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Adapted from https://github.com/turboderp/exllamav2 and
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https://github.com/turboderp/exllama
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*/
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#ifndef _matrix_view_cuh
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#define _matrix_view_cuh
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#include <cuda_runtime.h>
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#include <cuda_fp16.h>
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#include "qdq_util.cuh"
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namespace vllm {
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namespace gptq {
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class MatrixView_half {
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public:
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const half* data;
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const int height;
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const int width;
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__device__ __forceinline__ MatrixView_half(const half* data, const int height,
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const int width)
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: data(data), height(height), width(width) {}
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__device__ __forceinline__ half item(int row, int column) const {
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return data[row * width + column];
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}
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__device__ __forceinline__ half2 item_half2(int row, int column) const {
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return ((half2*)data)[(row * width + column) / 2];
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}
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__device__ __forceinline__ half2 item_half2half2(int row, int column) const {
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return __half2half2(data[row * width + column]);
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}
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__device__ __forceinline__ const half* item_ptr(int row, int column) const {
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return &data[row * width + column];
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}
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__device__ __forceinline__ void item4(half (&items)[4], int row,
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int column) const {
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half2* ptr = (half2*)item_ptr(row, column);
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half2 i01 = ptr[0];
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half2 i23 = ptr[1];
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items[0] = __low2half(i01);
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items[1] = __high2half(i01);
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items[2] = __low2half(i23);
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items[3] = __high2half(i23);
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}
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__device__ __forceinline__ void item4_f(float (&items)[4], int row,
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int column) const {
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half2* ptr = (half2*)item_ptr(row, column);
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half2 i01 = ptr[0];
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half2 i23 = ptr[1];
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items[0] = __half2float(__low2half(i01));
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items[1] = __half2float(__high2half(i01));
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items[2] = __half2float(__low2half(i23));
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items[3] = __half2float(__high2half(i23));
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}
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__device__ __forceinline__ void item4_h2(half2 (&items)[4], int row,
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int column) const {
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half2* ptr = (half2*)item_ptr(row, column);
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half2 i01 = ptr[0];
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half2 i23 = ptr[1];
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items[0] = __half2half2(__low2half(i01));
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items[1] = __half2half2(__high2half(i01));
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items[2] = __half2half2(__low2half(i23));
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items[3] = __half2half2(__high2half(i23));
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}
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};
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class MatrixView_half_rw {
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public:
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half* data;
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const int height;
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const int width;
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__device__ __forceinline__ MatrixView_half_rw(half* data, const int height,
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const int width)
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: data(data), height(height), width(width) {}
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__device__ __forceinline__ half item(int row, int column) const {
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return data[row * width + column];
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}
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__device__ __forceinline__ half2 item_half2(int row, int column) const {
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return ((half2*)data)[(row * width + column) / 2];
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}
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__device__ __forceinline__ half* item_ptr(int row, int column) {
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return &data[row * width + column];
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}
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__device__ __forceinline__ void set(int row, int column, half value) {
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data[row * width + column] = value;
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}
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__device__ __forceinline__ void set_half2(int row, int column, half2 value) {
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((half2*)data)[(row * width + column) / 2] = value;
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}
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__device__ __forceinline__ void set4(int row, int column, half v0, half v1,
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half v2, half v3) {
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half2 v01 = __halves2half2(v0, v1);
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half2 v23 = __halves2half2(v2, v3);
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half2* ptr = (half2*)item_ptr(row, column);
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ptr[0] = v01;
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ptr[1] = v23;
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}
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};
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class MatrixView_q4_row {
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public:
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const uint32_t* data;
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const int height;
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const int width;
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__device__ __forceinline__ MatrixView_q4_row(const uint32_t* data,
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const int height,
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const int width)
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: data(data), height(height), width(width) {}
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__device__ __forceinline__ int item(int row, int column) const {
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int shift = (column & 0x07) * 4;
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return (data[row * width / 8 + column / 8] >> shift) & 0x0f;
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}
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__device__ __forceinline__ void item2(int (&items)[2], int row,
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int column) const {
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int shift = (column & 0x07) * 4;
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uint32_t d = data[row * width / 8 + column / 8] >> shift;
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items[0] = d & 0x0f;
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items[1] = (d >> 4) & 0x0f;
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}
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__device__ __forceinline__ void item4(int (&items)[4], int row,
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int column) const {
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int shift = (column & 0x07) * 4;
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uint32_t d = data[row * width / 8 + column / 8] >> shift;
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items[0] = d & 0x0f;
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items[1] = (d >> 4) & 0x0f;
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items[2] = (d >> 8) & 0x0f;
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items[3] = (d >> 12) & 0x0f;
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}
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};
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class MatrixView_q4_column {
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public:
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const uint32_t* data;
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const int height;
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const int width;
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__device__ __forceinline__ MatrixView_q4_column(const uint32_t* data,
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const int height,
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const int width)
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: data(data), height(height), width(width) {}
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__device__ __forceinline__ int item(int row, int column) const {
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int shift = (row & 0x07) * 4;
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return (data[row / 8 * width + column] >> shift) & 0x0f;
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}
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__device__ __forceinline__ uint32_t item_uint32_t(int row, int column) {
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return data[row / 8 * width + column];
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}
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__device__ __forceinline__ const uint32_t* item_uint32_ptr(int row,
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int column) {
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return &data[row / 8 * width + column];
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}
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};
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class MatrixView_q2_row {
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public:
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const uint32_t* data;
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const int height;
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const int width;
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__device__ __forceinline__ MatrixView_q2_row(const uint32_t* data,
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const int height,
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const int width)
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: data(data), height(height), width(width) {}
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__device__ __forceinline__ int item(int row, int column) const {
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int shift = (column & 0x0f) * 2;
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return (data[row * width / 16 + column / 16] >> shift) & 0x03;
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}
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__device__ __forceinline__ void item2(int (&items)[2], int row,
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int column) const {
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int shift = (column & 0x0f) * 2;
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uint32_t d = data[row * width / 16 + column / 16] >> shift;
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items[0] = d & 0x03;
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items[1] = (d >> 2) & 0x03;
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}
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__device__ __forceinline__ void item4(int (&items)[4], int row,
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int column) const {
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int shift = (column & 0x0f) * 2;
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uint32_t d = data[row * width / 16 + column / 16] >> shift;
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items[0] = d & 0x03;
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items[1] = (d >> 2) & 0x03;
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items[2] = (d >> 4) & 0x03;
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items[3] = (d >> 6) & 0x03;
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}
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};
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class MatrixView_q3_row {
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public:
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const uint32_t* data;
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const int height;
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const int width;
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__device__ __forceinline__ MatrixView_q3_row(const uint32_t* data,
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const int height,
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const int width)
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: data(data), height(height), width(width) {}
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__device__ __forceinline__ int item(int row, int column) const {
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int z_w = column * 3 / 32;
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int z_mod = column & 0x1f;
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if (z_mod == 10) {
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return (data[row * width * 3 / 32 + z_w] >> 30) |
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((data[row * width * 3 / 32 + (z_w + 1)] << 2) & 0x4);
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} else if (z_mod == 21) {
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return (data[row * width * 3 / 32 + z_w] >> 31) |
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((data[row * width * 3 / 32 + (z_w + 1)] << 1) & 0x6);
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} else if (z_mod < 10) {
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return (data[row * width * 3 / 32 + z_w] >> (z_mod * 3)) & 0x07;
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} else if (z_mod < 21) {
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return (data[row * width * 3 / 32 + z_w] >> (z_mod * 3 - 32)) & 0x07;
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} else {
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return (data[row * width * 3 / 32 + z_w] >> (z_mod * 3 - 64)) & 0x07;
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}
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}
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__device__ __forceinline__ void item4(int (&items)[4], int row,
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int column) const {
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int shift = (column & 0x1f);
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uint32_t d;
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if (shift <= 4) {
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d = data[row * width / 32 * 3 + column * 3 / 32] >> (shift * 3);
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} else if (shift == 8) {
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d = (data[row * width / 32 * 3 + column * 3 / 32] >> 24) |
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((data[row * width / 32 * 3 + column * 3 / 32 + 1] & 0x0f) << 8);
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} else if (shift <= 16) {
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d = data[row * width / 32 * 3 + column * 3 / 32] >> (shift * 3 - 32);
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} else if (shift == 20) {
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d = (data[row * width / 32 * 3 + column * 3 / 32] >> 28) |
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((data[row * width / 32 * 3 + column * 3 / 32 + 1] & 0xff) << 4);
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} else {
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d = data[row * width / 32 * 3 + column * 3 / 32] >> (shift * 3 - 64);
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}
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items[0] = d & 0x07;
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items[1] = (d >> 3) & 0x07;
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items[2] = (d >> 6) & 0x07;
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items[3] = (d >> 9) & 0x07;
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}
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};
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class MatrixView_q8_row {
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public:
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const uint32_t* data;
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const int height;
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const int width;
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__device__ __forceinline__ MatrixView_q8_row(const uint32_t* data,
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const int height,
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const int width)
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: data(data), height(height), width(width) {}
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__device__ __forceinline__ int item(int row, int column) const {
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int shift = (column & 0x03) * 8;
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return (data[row * width / 4 + column / 4] >> shift) & 0xff;
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}
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__device__ __forceinline__ void item2(int (&items)[2], int row,
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int column) const {
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int shift = (column & 0x03) * 8;
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uint32_t d = data[row * width / 4 + column / 4] >> shift;
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items[0] = d & 0xff;
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items[1] = (d >> 8) & 0xff;
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}
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__device__ __forceinline__ void item4(int (&items)[4], int row,
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int column) const {
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int shift = (column & 0x03) * 2;
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uint32_t d = data[row * width / 4 + column / 4] >> shift;
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items[0] = d & 0xff;
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items[1] = (d >> 8) & 0xff;
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items[2] = (d >> 16) & 0xff;
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items[3] = (d >> 24) & 0xff;
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}
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};
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} // namespace gptq
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} // namespace vllm
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#endif
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