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metal : minor code formatting

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Georgi Gerganov 2024-11-25 15:08:04 +02:00
parent 5a8987793f
commit b756441104
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2 changed files with 321 additions and 316 deletions
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ggml/src/ggml-metal/ggml-metal.m
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@ -1951,316 +1951,316 @@ static void ggml_metal_encode_node(
} }
#endif #endif
// for now the matrix-matrix multiplication kernel only works on A14+/M1+ SoCs // for now the matrix-matrix multiplication kernel only works on A14+/M1+ SoCs
// AMD GPU and older A-chips will reuse matrix-vector multiplication kernel // AMD GPU and older A-chips will reuse matrix-vector multiplication kernel
if ([device supportsFamily:MTLGPUFamilyApple7] && if ([device supportsFamily:MTLGPUFamilyApple7] &&
!ggml_is_transposed(src0) && !ggml_is_transposed(src0) &&
!ggml_is_transposed(src1) && !ggml_is_transposed(src1) &&
src1t == GGML_TYPE_F32 && src1t == GGML_TYPE_F32 &&
ne00 % 32 == 0 && ne00 >= 64 && ne00 % 32 == 0 && ne00 >= 64 &&
(ne11 > ne11_mm_min || (ggml_is_quantized(src0t) && ne12 > 1))) { (ne11 > ne11_mm_min || (ggml_is_quantized(src0t) && ne12 > 1))) {
//printf("matrix: ne00 = %6d, ne01 = %6d, ne02 = %6d, ne11 = %6d, ne12 = %6d\n", ne00, ne01, ne02, ne11, ne12); //printf("matrix: ne00 = %6d, ne01 = %6d, ne02 = %6d, ne11 = %6d, ne12 = %6d\n", ne00, ne01, ne02, ne11, ne12);
// some Metal matrix data types require aligned pointers // some Metal matrix data types require aligned pointers
// ref: https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf (Table 2.5) // ref: https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf (Table 2.5)
switch (src0->type) { switch (src0->type) {
case GGML_TYPE_F32: GGML_ASSERT(nb01 % 16 == 0); break; case GGML_TYPE_F32: GGML_ASSERT(nb01 % 16 == 0); break;
case GGML_TYPE_F16: GGML_ASSERT(nb01 % 8 == 0); break; case GGML_TYPE_F16: GGML_ASSERT(nb01 % 8 == 0); break;
case GGML_TYPE_BF16: GGML_ASSERT(nb01 % 8 == 0); break; case GGML_TYPE_BF16: GGML_ASSERT(nb01 % 8 == 0); break;
default: break; default: break;
} }
id<MTLComputePipelineState> pipeline = nil; id<MTLComputePipelineState> pipeline = nil;
switch (src0->type) { switch (src0->type) {
case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_F32_F32 ].pipeline; break; case GGML_TYPE_F32: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_F32_F32 ].pipeline; break;
case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_F16_F32 ].pipeline; break; case GGML_TYPE_F16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_F16_F32 ].pipeline; break;
case GGML_TYPE_BF16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_BF16_F32 ].pipeline; break; case GGML_TYPE_BF16: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_BF16_F32 ].pipeline; break;
case GGML_TYPE_Q4_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_0_F32 ].pipeline; break; case GGML_TYPE_Q4_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_0_F32 ].pipeline; break;
case GGML_TYPE_Q4_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_1_F32 ].pipeline; break; case GGML_TYPE_Q4_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_1_F32 ].pipeline; break;
case GGML_TYPE_Q5_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_0_F32 ].pipeline; break; case GGML_TYPE_Q5_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_0_F32 ].pipeline; break;
case GGML_TYPE_Q5_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_1_F32 ].pipeline; break; case GGML_TYPE_Q5_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_1_F32 ].pipeline; break;
case GGML_TYPE_Q8_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q8_0_F32 ].pipeline; break; case GGML_TYPE_Q8_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q8_0_F32 ].pipeline; break;
case GGML_TYPE_Q2_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q2_K_F32 ].pipeline; break; case GGML_TYPE_Q2_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q2_K_F32 ].pipeline; break;
case GGML_TYPE_Q3_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q3_K_F32 ].pipeline; break; case GGML_TYPE_Q3_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q3_K_F32 ].pipeline; break;
case GGML_TYPE_Q4_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_K_F32 ].pipeline; break; case GGML_TYPE_Q4_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_K_F32 ].pipeline; break;
case GGML_TYPE_Q5_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_K_F32 ].pipeline; break; case GGML_TYPE_Q5_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_K_F32 ].pipeline; break;
case GGML_TYPE_Q6_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q6_K_F32 ].pipeline; break; case GGML_TYPE_Q6_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q6_K_F32 ].pipeline; break;
case GGML_TYPE_IQ2_XXS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_XXS_F32].pipeline; break; case GGML_TYPE_IQ2_XXS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_XXS_F32].pipeline; break;
case GGML_TYPE_IQ2_XS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_XS_F32 ].pipeline; break; case GGML_TYPE_IQ2_XS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_XS_F32 ].pipeline; break;
case GGML_TYPE_IQ3_XXS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ3_XXS_F32].pipeline; break; case GGML_TYPE_IQ3_XXS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ3_XXS_F32].pipeline; break;
case GGML_TYPE_IQ3_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ3_S_F32 ].pipeline; break; case GGML_TYPE_IQ3_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ3_S_F32 ].pipeline; break;
case GGML_TYPE_IQ2_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_S_F32 ].pipeline; break; case GGML_TYPE_IQ2_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ2_S_F32 ].pipeline; break;
case GGML_TYPE_IQ1_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ1_S_F32 ].pipeline; break; case GGML_TYPE_IQ1_S: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ1_S_F32 ].pipeline; break;
case GGML_TYPE_IQ1_M: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ1_M_F32 ].pipeline; break; case GGML_TYPE_IQ1_M: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ1_M_F32 ].pipeline; break;
case GGML_TYPE_IQ4_NL: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ4_NL_F32 ].pipeline; break; case GGML_TYPE_IQ4_NL: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ4_NL_F32 ].pipeline; break;
case GGML_TYPE_IQ4_XS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ4_XS_F32 ].pipeline; break; case GGML_TYPE_IQ4_XS: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_IQ4_XS_F32 ].pipeline; break;
default: GGML_ABORT("MUL MAT-MAT not implemented"); default: GGML_ABORT("MUL MAT-MAT not implemented");
} }
ggml_metal_kargs_mul_mm args = { ggml_metal_kargs_mul_mm args = {
/*.ne00 =*/ ne00, /*.ne00 =*/ ne00,
/*.ne02 =*/ ne02, /*.ne02 =*/ ne02,
/*.nb01 =*/ nb01, /*.nb01 =*/ nb01,
/*.nb02 =*/ nb02, /*.nb02 =*/ nb02,
/*.nb03 =*/ nb03, /*.nb03 =*/ nb03,
/*.ne12 =*/ ne12, /*.ne12 =*/ ne12,
/*.nb10 =*/ nb10, /*.nb10 =*/ nb10,
/*.nb11 =*/ nb11, /*.nb11 =*/ nb11,
/*.nb12 =*/ nb12, /*.nb12 =*/ nb12,
/*.nb13 =*/ nb13, /*.nb13 =*/ nb13,
/*.ne0 =*/ ne0, /*.ne0 =*/ ne0,
/*.ne1 =*/ ne1, /*.ne1 =*/ ne1,
/*.r2 =*/ r2, /*.r2 =*/ r2,
/*.r3 =*/ r3, /*.r3 =*/ r3,
}; };
[encoder setComputePipelineState:pipeline]; [encoder setComputePipelineState:pipeline];
[encoder setBytes:&args length:sizeof(args) atIndex:0]; [encoder setBytes:&args length:sizeof(args) atIndex:0];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1];
[encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2];
[encoder setBuffer:id_dst offset:offs_dst atIndex:3]; [encoder setBuffer:id_dst offset:offs_dst atIndex:3];
[encoder setThreadgroupMemoryLength:8192 atIndex:0]; [encoder setThreadgroupMemoryLength:8192 atIndex:0];
[encoder dispatchThreadgroups:MTLSizeMake( (ne11 + 31)/32, (ne01 + 63)/64, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(128, 1, 1)]; [encoder dispatchThreadgroups:MTLSizeMake( (ne11 + 31)/32, (ne01 + 63)/64, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(128, 1, 1)];
} else { } else {
int nth0 = 32; int nth0 = 32;
int nth1 = 1; int nth1 = 1;
int nrows = 1; int nrows = 1;
//printf("vector: ne00 = %6d, ne01 = %6d, ne02 = %6d, ne11 = %6d, ne12 = %6d\n", ne00, ne01, ne02, ne11, ne12); //printf("vector: ne00 = %6d, ne01 = %6d, ne02 = %6d, ne11 = %6d, ne12 = %6d\n", ne00, ne01, ne02, ne11, ne12);
id<MTLComputePipelineState> pipeline = nil; id<MTLComputePipelineState> pipeline = nil;
// use custom matrix x vector kernel // use custom matrix x vector kernel
switch (src0t) { switch (src0t) {
case GGML_TYPE_F32: case GGML_TYPE_F32:
{ {
GGML_ASSERT(src1t == GGML_TYPE_F32); GGML_ASSERT(src1t == GGML_TYPE_F32);
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F32_F32].pipeline; pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F32_F32].pipeline;
nrows = 4;
} break;
case GGML_TYPE_F16:
{
nth0 = 32;
nth1 = 1;
if (src1t == GGML_TYPE_F32) {
if (ne11 * ne12 < 4) {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_1ROW].pipeline;
} else if (ne00 >= 128 && ne01 >= 8 && ne00%4 == 0) {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_L4].pipeline;
nrows = ne11;
} else {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32].pipeline;
nrows = 4; nrows = 4;
} break;
case GGML_TYPE_F16:
{
nth0 = 32;
nth1 = 1;
if (src1t == GGML_TYPE_F32) {
if (ne11 * ne12 < 4) {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_1ROW].pipeline;
} else if (ne00 >= 128 && ne01 >= 8 && ne00%4 == 0) {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32_L4].pipeline;
nrows = ne11;
} else {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32].pipeline;
nrows = 4;
}
} else {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F16].pipeline;
nrows = 4;
}
} break;
case GGML_TYPE_BF16:
{
nth0 = 32;
nth1 = 1;
if (src1t == GGML_TYPE_F32) {
if (ne11 * ne12 < 4) {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_1ROW].pipeline;
} else if (ne00 >= 128 && ne01 >= 8 && ne00%4 == 0) {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_L4].pipeline;
nrows = ne11;
} else {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32].pipeline;
nrows = 4;
}
} else {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_BF16].pipeline;
nrows = 4;
}
} break;
case GGML_TYPE_Q4_0:
{
nth0 = 8;
nth1 = 8;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_0_F32].pipeline;
} break;
case GGML_TYPE_Q4_1:
{
nth0 = 8;
nth1 = 8;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_1_F32].pipeline;
} break;
case GGML_TYPE_Q5_0:
{
nth0 = 8;
nth1 = 8;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_0_F32].pipeline;
} break;
case GGML_TYPE_Q5_1:
{
nth0 = 8;
nth1 = 8;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_1_F32].pipeline;
} break;
case GGML_TYPE_Q8_0:
{
nth0 = 8;
nth1 = 8;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q8_0_F32].pipeline;
} break;
case GGML_TYPE_Q2_K:
{
nth0 = 2;
nth1 = 32;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q2_K_F32].pipeline;
} break;
case GGML_TYPE_Q3_K:
{
nth0 = 2;
nth1 = 32;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q3_K_F32].pipeline;
} break;
case GGML_TYPE_Q4_K:
{
nth0 = 4; //1;
nth1 = 8; //32;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_K_F32].pipeline;
} break;
case GGML_TYPE_Q5_K:
{
nth0 = 2;
nth1 = 32;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_K_F32].pipeline;
} break;
case GGML_TYPE_Q6_K:
{
nth0 = 2;
nth1 = 32;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q6_K_F32].pipeline;
} break;
case GGML_TYPE_IQ2_XXS:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_XXS_F32].pipeline;
} break;
case GGML_TYPE_IQ2_XS:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_XS_F32].pipeline;
} break;
case GGML_TYPE_IQ3_XXS:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ3_XXS_F32].pipeline;
} break;
case GGML_TYPE_IQ3_S:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ3_S_F32].pipeline;
} break;
case GGML_TYPE_IQ2_S:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_S_F32].pipeline;
} break;
case GGML_TYPE_IQ1_S:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ1_S_F32].pipeline;
} break;
case GGML_TYPE_IQ1_M:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ1_M_F32].pipeline;
} break;
case GGML_TYPE_IQ4_NL:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ4_NL_F32].pipeline;
} break;
case GGML_TYPE_IQ4_XS:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ4_XS_F32].pipeline;
} break;
default:
{
GGML_LOG_ERROR("Asserting on type %d\n", (int)src0t);
GGML_ABORT("not implemented");
} }
}; } else {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F16].pipeline;
nrows = 4;
}
} break;
case GGML_TYPE_BF16:
{
nth0 = 32;
nth1 = 1;
if (src1t == GGML_TYPE_F32) {
if (ne11 * ne12 < 4) {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_1ROW].pipeline;
} else if (ne00 >= 128 && ne01 >= 8 && ne00%4 == 0) {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32_L4].pipeline;
nrows = ne11;
} else {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_F32].pipeline;
nrows = 4;
}
} else {
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_BF16_BF16].pipeline;
nrows = 4;
}
} break;
case GGML_TYPE_Q4_0:
{
nth0 = 8;
nth1 = 8;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_0_F32].pipeline;
} break;
case GGML_TYPE_Q4_1:
{
nth0 = 8;
nth1 = 8;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_1_F32].pipeline;
} break;
case GGML_TYPE_Q5_0:
{
nth0 = 8;
nth1 = 8;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_0_F32].pipeline;
} break;
case GGML_TYPE_Q5_1:
{
nth0 = 8;
nth1 = 8;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_1_F32].pipeline;
} break;
case GGML_TYPE_Q8_0:
{
nth0 = 8;
nth1 = 8;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q8_0_F32].pipeline;
} break;
case GGML_TYPE_Q2_K:
{
nth0 = 2;
nth1 = 32;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q2_K_F32].pipeline;
} break;
case GGML_TYPE_Q3_K:
{
nth0 = 2;
nth1 = 32;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q3_K_F32].pipeline;
} break;
case GGML_TYPE_Q4_K:
{
nth0 = 4; //1;
nth1 = 8; //32;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_K_F32].pipeline;
} break;
case GGML_TYPE_Q5_K:
{
nth0 = 2;
nth1 = 32;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_K_F32].pipeline;
} break;
case GGML_TYPE_Q6_K:
{
nth0 = 2;
nth1 = 32;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q6_K_F32].pipeline;
} break;
case GGML_TYPE_IQ2_XXS:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_XXS_F32].pipeline;
} break;
case GGML_TYPE_IQ2_XS:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_XS_F32].pipeline;
} break;
case GGML_TYPE_IQ3_XXS:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ3_XXS_F32].pipeline;
} break;
case GGML_TYPE_IQ3_S:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ3_S_F32].pipeline;
} break;
case GGML_TYPE_IQ2_S:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ2_S_F32].pipeline;
} break;
case GGML_TYPE_IQ1_S:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ1_S_F32].pipeline;
} break;
case GGML_TYPE_IQ1_M:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ1_M_F32].pipeline;
} break;
case GGML_TYPE_IQ4_NL:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ4_NL_F32].pipeline;
} break;
case GGML_TYPE_IQ4_XS:
{
nth0 = 4;
nth1 = 16;
pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_IQ4_XS_F32].pipeline;
} break;
default:
{
GGML_LOG_ERROR("Asserting on type %d\n", (int)src0t);
GGML_ABORT("not implemented");
}
};
ggml_metal_kargs_mul_mv args = { ggml_metal_kargs_mul_mv args = {
/*.ne00 =*/ ne00, /*.ne00 =*/ ne00,
/*.ne01 =*/ ne01, /*.ne01 =*/ ne01,
/*.ne02 =*/ ne02, /*.ne02 =*/ ne02,
/*.nb00 =*/ nb00, /*.nb00 =*/ nb00,
/*.nb01 =*/ nb01, /*.nb01 =*/ nb01,
/*.nb02 =*/ nb02, /*.nb02 =*/ nb02,
/*.nb03 =*/ nb03, /*.nb03 =*/ nb03,
/*.ne10 =*/ ne10, /*.ne10 =*/ ne10,
/*.ne11 =*/ ne11, /*.ne11 =*/ ne11,
/*.ne12 =*/ ne12, /*.ne12 =*/ ne12,
/*.nb10 =*/ nb10, /*.nb10 =*/ nb10,
/*.nb11 =*/ nb11, /*.nb11 =*/ nb11,
/*.nb12 =*/ nb12, /*.nb12 =*/ nb12,
/*.nb13 =*/ nb13, /*.nb13 =*/ nb13,
/*.ne0 =*/ ne0, /*.ne0 =*/ ne0,
/*.ne1 =*/ ne1, /*.ne1 =*/ ne1,
/*.r2 =*/ r2, /*.r2 =*/ r2,
/*.r3 =*/ r3, /*.r3 =*/ r3,
}; };
[encoder setComputePipelineState:pipeline]; [encoder setComputePipelineState:pipeline];
[encoder setBytes:&args length:sizeof(args) atIndex:0]; [encoder setBytes:&args length:sizeof(args) atIndex:0];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1];
[encoder setBuffer:id_src1 offset:offs_src1 atIndex:2]; [encoder setBuffer:id_src1 offset:offs_src1 atIndex:2];
[encoder setBuffer:id_dst offset:offs_dst atIndex:3]; [encoder setBuffer:id_dst offset:offs_dst atIndex:3];
if (src0t == GGML_TYPE_Q4_0 || src0t == GGML_TYPE_Q4_1 || src0t == GGML_TYPE_Q5_0 || if (src0t == GGML_TYPE_Q4_0 || src0t == GGML_TYPE_Q4_1 || src0t == GGML_TYPE_Q5_0 ||
src0t == GGML_TYPE_Q5_1 || src0t == GGML_TYPE_Q8_0 || src0t == GGML_TYPE_Q2_K || src0t == GGML_TYPE_Q5_1 || src0t == GGML_TYPE_Q8_0 || src0t == GGML_TYPE_Q2_K ||
src0t == GGML_TYPE_IQ1_S || src0t == GGML_TYPE_IQ1_M || src0t == GGML_TYPE_IQ2_S) { src0t == GGML_TYPE_IQ1_S || src0t == GGML_TYPE_IQ1_M || src0t == GGML_TYPE_IQ2_S) {
[encoder dispatchThreadgroups:MTLSizeMake((ne01 + 7)/8, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)]; [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 7)/8, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
} }
else if (src0t == GGML_TYPE_IQ2_XXS || src0t == GGML_TYPE_IQ2_XS) { else if (src0t == GGML_TYPE_IQ2_XXS || src0t == GGML_TYPE_IQ2_XS) {
const int mem_size = src0t == GGML_TYPE_IQ2_XXS ? 256*8+128 : 512*8+128; const int mem_size = src0t == GGML_TYPE_IQ2_XXS ? 256*8+128 : 512*8+128;
[encoder setThreadgroupMemoryLength:mem_size atIndex:0]; [encoder setThreadgroupMemoryLength:mem_size atIndex:0];
[encoder dispatchThreadgroups:MTLSizeMake((ne01 + 7)/8, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)]; [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 7)/8, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
} }
else if (src0t == GGML_TYPE_IQ3_XXS || src0t == GGML_TYPE_IQ3_S) { else if (src0t == GGML_TYPE_IQ3_XXS || src0t == GGML_TYPE_IQ3_S) {
const int mem_size = src0t == GGML_TYPE_IQ3_XXS ? 256*4+128 : 512*4; const int mem_size = src0t == GGML_TYPE_IQ3_XXS ? 256*4+128 : 512*4;
[encoder setThreadgroupMemoryLength:mem_size atIndex:0]; [encoder setThreadgroupMemoryLength:mem_size atIndex:0];
[encoder dispatchThreadgroups:MTLSizeMake((ne01 + 7)/8, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)]; [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 7)/8, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
} }
else if (src0t == GGML_TYPE_IQ4_NL || src0t == GGML_TYPE_IQ4_XS) { else if (src0t == GGML_TYPE_IQ4_NL || src0t == GGML_TYPE_IQ4_XS) {
const int mem_size = 32*sizeof(float); const int mem_size = 32*sizeof(float);
[encoder setThreadgroupMemoryLength:mem_size atIndex:0]; [encoder setThreadgroupMemoryLength:mem_size atIndex:0];
[encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)]; [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
} }
else if (src0t == GGML_TYPE_Q4_K) { else if (src0t == GGML_TYPE_Q4_K) {
[encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)]; [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
} }
else if (src0t == GGML_TYPE_Q3_K) { else if (src0t == GGML_TYPE_Q3_K) {
[encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)]; [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
} }
else if (src0t == GGML_TYPE_Q5_K) { else if (src0t == GGML_TYPE_Q5_K) {
[encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)]; [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
} }
else if (src0t == GGML_TYPE_Q6_K) { else if (src0t == GGML_TYPE_Q6_K) {
[encoder dispatchThreadgroups:MTLSizeMake((ne01 + 1)/2, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)]; [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 1)/2, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
} else { } else {
const int64_t ny = (ne11 + nrows - 1)/nrows; const int64_t ny = (ne11 + nrows - 1)/nrows;
[encoder dispatchThreadgroups:MTLSizeMake(ne01, ny, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)]; [encoder dispatchThreadgroups:MTLSizeMake(ne01, ny, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
} }
} }
} break; } break;
case GGML_OP_MUL_MAT_ID: case GGML_OP_MUL_MAT_ID:
{ {

43
ggml/src/ggml-metal/ggml-metal.metal
View File

@ -5447,12 +5447,12 @@ kernel void kernel_mul_mm(
const int im = tgpig.z; const int im = tgpig.z;
// if this block is of 64x32 shape or smaller // if this block is of 64x32 shape or smaller
short n_rows = (args.ne0 - r0*BLOCK_SIZE_M < BLOCK_SIZE_M) ? (args.ne0 - r0*BLOCK_SIZE_M) : BLOCK_SIZE_M; const short n_rows = (args.ne0 - r0*BLOCK_SIZE_M < BLOCK_SIZE_M) ? (args.ne0 - r0*BLOCK_SIZE_M) : BLOCK_SIZE_M;
short n_cols = (args.ne1 - r1*BLOCK_SIZE_N < BLOCK_SIZE_N) ? (args.ne1 - r1*BLOCK_SIZE_N) : BLOCK_SIZE_N; const short n_cols = (args.ne1 - r1*BLOCK_SIZE_N < BLOCK_SIZE_N) ? (args.ne1 - r1*BLOCK_SIZE_N) : BLOCK_SIZE_N;
// a thread shouldn't load data outside of the matrix // a thread shouldn't load data outside of the matrix
short thread_row = ((short)tiitg/THREAD_PER_ROW) < n_rows ? ((short)tiitg/THREAD_PER_ROW) : n_rows - 1; const short thread_row = ((short)tiitg/THREAD_PER_ROW) < n_rows ? ((short)tiitg/THREAD_PER_ROW) : n_rows - 1;
short thread_col = ((short)tiitg/THREAD_PER_COL) < n_cols ? ((short)tiitg/THREAD_PER_COL) : n_cols - 1; const short thread_col = ((short)tiitg/THREAD_PER_COL) < n_cols ? ((short)tiitg/THREAD_PER_COL) : n_cols - 1;
simdgroup_T8x8 ma[4]; simdgroup_T8x8 ma[4];
simdgroup_float8x8 mb[2]; simdgroup_float8x8 mb[2];
@ -5467,20 +5467,23 @@ kernel void kernel_mul_mm(
const int i12 = im%args.ne12; const int i12 = im%args.ne12;
const int i13 = im/args.ne12; const int i13 = im/args.ne12;
uint64_t offset0 = (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03; const uint64_t offset0 = (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
short offset1 = il/nl; const short offset1 = il/nl;
device const block_q * x = (device const block_q *)(src0
+ args.nb01*(r0*BLOCK_SIZE_M + thread_row) + offset0) + offset1;
device const block_q * x = (device const block_q *)(src0 + (r0*BLOCK_SIZE_M + thread_row)*args.nb01 + offset0) + offset1;
device const float * y = (device const float *)(src1 device const float * y = (device const float *)(src1
+ args.nb13*i13 + args.nb13*i13
+ args.nb12*i12 + args.nb12*i12
+ args.nb11*(r1 * BLOCK_SIZE_N + thread_col) + args.nb11*(r1*BLOCK_SIZE_N + thread_col)
+ args.nb10*(BLOCK_SIZE_K / THREAD_PER_COL * (tiitg % THREAD_PER_COL))); + args.nb10*(BLOCK_SIZE_K / THREAD_PER_COL * (tiitg % THREAD_PER_COL)));
for (int loop_k = 0; loop_k < args.ne00; loop_k += BLOCK_SIZE_K) { for (int loop_k = 0; loop_k < args.ne00; loop_k += BLOCK_SIZE_K) {
// load data and store to threadgroup memory // load data and store to threadgroup memory
T4x4 temp_a; T4x4 temp_a;
dequantize_func(x, il, temp_a); dequantize_func(x, il, temp_a);
threadgroup_barrier(mem_flags::mem_threadgroup); threadgroup_barrier(mem_flags::mem_threadgroup);
#pragma unroll(16) #pragma unroll(16)
@ -5490,44 +5493,46 @@ kernel void kernel_mul_mm(
+ (tiitg/THREAD_PER_ROW)%8 + (i&7)*8) = temp_a[i/4][i%4]; + (tiitg/THREAD_PER_ROW)%8 + (i&7)*8) = temp_a[i/4][i%4];
} }
*(threadgroup float2x4 *)(sb + (tiitg % THREAD_PER_COL)*8*32 + 8*(tiitg/THREAD_PER_COL)) = *((device float2x4 *) y); *(threadgroup float2x4 *)(sb + 32*8*(tiitg%THREAD_PER_COL) + 8*(tiitg/THREAD_PER_COL)) = *((device float2x4 *) y);
il = (il + 2 < nl) ? il + 2 : il % 2; il = (il + 2 < nl) ? il + 2 : il % 2;
x = (il < 2) ? x + (2+nl-1)/nl : x; x = (il < 2) ? x + (2 + nl - 1)/nl : x;
y += BLOCK_SIZE_K; y += BLOCK_SIZE_K;
threadgroup_barrier(mem_flags::mem_threadgroup); threadgroup_barrier(mem_flags::mem_threadgroup);
// load matrices from threadgroup memory and conduct outer products // load matrices from threadgroup memory and conduct outer products
threadgroup T * lsma = (sa + THREAD_MAT_M*SG_MAT_SIZE*(sgitg%2)); threadgroup const T * lsma = (sa + THREAD_MAT_M*SG_MAT_SIZE*(sgitg%2));
threadgroup float * lsmb = (sb + THREAD_MAT_N*SG_MAT_SIZE*(sgitg/2)); threadgroup const float * lsmb = (sb + THREAD_MAT_N*SG_MAT_SIZE*(sgitg/2));
#pragma unroll(4) #pragma unroll(4)
for (short ik = 0; ik < BLOCK_SIZE_K / 8; ik++) { for (short ik = 0; ik < BLOCK_SIZE_K/8; ik++) {
#pragma unroll(4) #pragma unroll(4)
for (short i = 0; i < 4; i++) { for (short i = 0; i < 4; i++) {
simdgroup_load(ma[i], lsma + SG_MAT_SIZE * i); simdgroup_load(ma[i], lsma + SG_MAT_SIZE * i);
} }
simdgroup_barrier(mem_flags::mem_none); simdgroup_barrier(mem_flags::mem_none);
#pragma unroll(2) #pragma unroll(2)
for (short i = 0; i < 2; i++) { for (short i = 0; i < 2; i++) {
simdgroup_load(mb[i], lsmb + SG_MAT_SIZE * i); simdgroup_load(mb[i], lsmb + SG_MAT_SIZE * i);
} }
lsma += BLOCK_SIZE_M/SG_MAT_ROW * SG_MAT_SIZE;
lsmb += BLOCK_SIZE_N/SG_MAT_ROW * SG_MAT_SIZE;
#pragma unroll(8) #pragma unroll(8)
for (short i = 0; i < 8; i++){ for (short i = 0; i < 8; i++){
simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]); simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
} }
lsma += (BLOCK_SIZE_M/SG_MAT_ROW)*SG_MAT_SIZE;
lsmb += (BLOCK_SIZE_N/SG_MAT_ROW)*SG_MAT_SIZE;
} }
} }
if ((r0 + 1) * BLOCK_SIZE_M <= args.ne0 && (r1 + 1) * BLOCK_SIZE_N <= args.ne1) { if ((r0 + 1) * BLOCK_SIZE_M <= args.ne0 && (r1 + 1) * BLOCK_SIZE_N <= args.ne1) {
device float * C = (device float *) dst + device float * C = (device float *) dst +
(BLOCK_SIZE_M * r0 + 32 * (sgitg & 1)) + \ (BLOCK_SIZE_M * r0 + 32*(sgitg & 1)) + \
(BLOCK_SIZE_N * r1 + 16 * (sgitg >> 1)) * args.ne0 + im*args.ne1*args.ne0; (BLOCK_SIZE_N * r1 + 16*(sgitg >> 1)) * args.ne0 + im*args.ne1*args.ne0;
for (short i = 0; i < 8; i++) { for (short i = 0; i < 8; i++) {
simdgroup_store(mc[i], C + 8 * (i%4) + 8 * args.ne0 * (i/4), args.ne0); simdgroup_store(mc[i], C + 8 * (i%4) + 8 * args.ne0 * (i/4), args.ne0);
@ -5536,7 +5541,7 @@ kernel void kernel_mul_mm(
// block is smaller than 64x32, we should avoid writing data outside of the matrix // block is smaller than 64x32, we should avoid writing data outside of the matrix
threadgroup_barrier(mem_flags::mem_threadgroup); threadgroup_barrier(mem_flags::mem_threadgroup);
threadgroup float * temp_str = ((threadgroup float *) shmem) \ threadgroup float * temp_str = ((threadgroup float *) shmem) \
+ 32 * (sgitg&1) + (16 * (sgitg>>1))*BLOCK_SIZE_M; + 32*(sgitg&1) + (16*(sgitg >> 1))*BLOCK_SIZE_M;
for (short i = 0; i < 8; i++) { for (short i = 0; i < 8; i++) {
simdgroup_store(mc[i], temp_str + 8*(i%4) + 8*BLOCK_SIZE_M*(i/4), BLOCK_SIZE_M); simdgroup_store(mc[i], temp_str + 8*(i%4) + 8*BLOCK_SIZE_M*(i/4), BLOCK_SIZE_M);
} }