vllm/csrc/quantization/gptq/matrix_view.cuh

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