Merge branch 'master' into concedo_experimental
# Conflicts: # .devops/full.Dockerfile # .devops/main.Dockerfile # CMakeLists.txt
This commit is contained in:
Concedo
commit
01dc509038
4 changed files with 572 additions and 19 deletions
57
ggml-metal.m
57
ggml-metal.m
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@ -49,9 +49,15 @@ struct ggml_metal_context {
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GGML_METAL_DECL_KERNEL(diag_mask_inf);
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GGML_METAL_DECL_KERNEL(get_rows_f16);
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GGML_METAL_DECL_KERNEL(get_rows_q4_0);
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GGML_METAL_DECL_KERNEL(get_rows_q2_k);
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GGML_METAL_DECL_KERNEL(get_rows_q4_k);
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GGML_METAL_DECL_KERNEL(get_rows_q6_k);
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GGML_METAL_DECL_KERNEL(rms_norm);
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GGML_METAL_DECL_KERNEL(mul_mat_f16_f32);
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GGML_METAL_DECL_KERNEL(mul_mat_q4_0_f32);
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GGML_METAL_DECL_KERNEL(mul_mat_q2_k_f32);
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GGML_METAL_DECL_KERNEL(mul_mat_q4_k_f32);
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GGML_METAL_DECL_KERNEL(mul_mat_q6_k_f32);
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GGML_METAL_DECL_KERNEL(rope);
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GGML_METAL_DECL_KERNEL(cpy_f32_f16);
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GGML_METAL_DECL_KERNEL(cpy_f32_f32);
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@ -133,9 +139,15 @@ struct ggml_metal_context * ggml_metal_init(void) {
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GGML_METAL_ADD_KERNEL(diag_mask_inf);
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GGML_METAL_ADD_KERNEL(get_rows_f16);
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GGML_METAL_ADD_KERNEL(get_rows_q4_0);
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GGML_METAL_ADD_KERNEL(get_rows_q2_k);
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GGML_METAL_ADD_KERNEL(get_rows_q4_k);
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GGML_METAL_ADD_KERNEL(get_rows_q6_k);
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GGML_METAL_ADD_KERNEL(rms_norm);
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GGML_METAL_ADD_KERNEL(mul_mat_f16_f32);
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GGML_METAL_ADD_KERNEL(mul_mat_q4_0_f32);
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GGML_METAL_ADD_KERNEL(mul_mat_q2_k_f32);
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GGML_METAL_ADD_KERNEL(mul_mat_q4_k_f32);
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GGML_METAL_ADD_KERNEL(mul_mat_q6_k_f32);
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GGML_METAL_ADD_KERNEL(rope);
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GGML_METAL_ADD_KERNEL(cpy_f32_f16);
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GGML_METAL_ADD_KERNEL(cpy_f32_f32);
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@ -517,7 +529,38 @@ void ggml_metal_graph_compute(
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nth1 = 4;
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[encoder setComputePipelineState:ctx->pipeline_mul_mat_q4_0_f32];
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} break;
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default: GGML_ASSERT(false && "not implemented");
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case GGML_TYPE_Q2_K:
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{
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GGML_ASSERT(ne02 == 1);
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GGML_ASSERT(ne12 == 1);
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nth0 = 4;
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nth1 = 16;
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[encoder setComputePipelineState:ctx->pipeline_mul_mat_q2_k_f32];
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} break;
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case GGML_TYPE_Q4_K:
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{
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GGML_ASSERT(ne02 == 1);
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GGML_ASSERT(ne12 == 1);
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nth0 = 4;
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nth1 = 16;
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[encoder setComputePipelineState:ctx->pipeline_mul_mat_q4_k_f32];
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} break;
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case GGML_TYPE_Q6_K:
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{
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GGML_ASSERT(ne02 == 1);
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GGML_ASSERT(ne12 == 1);
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nth0 = 4;
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nth1 = 16;
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[encoder setComputePipelineState:ctx->pipeline_mul_mat_q6_k_f32];
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} break;
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default:
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{
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fprintf(stderr, "Asserting on type %d\n",(int)src0t);
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GGML_ASSERT(false && "not implemented");
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}
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};
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@ -540,6 +583,15 @@ void ggml_metal_graph_compute(
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if (src0t == GGML_TYPE_Q4_0) {
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[encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
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[encoder dispatchThreadgroups:MTLSizeMake(ne01, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
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} else if (src0t == GGML_TYPE_Q2_K) {
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[encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
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[encoder dispatchThreadgroups:MTLSizeMake(ne01, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
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} else if (src0t == GGML_TYPE_Q4_K) {
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[encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
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[encoder dispatchThreadgroups:MTLSizeMake(ne01, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
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} else if (src0t == GGML_TYPE_Q6_K) {
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[encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
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[encoder dispatchThreadgroups:MTLSizeMake(ne01, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
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} else {
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[encoder setThreadgroupMemoryLength:nth0*sizeof(float) atIndex:0];
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[encoder dispatchThreadgroups:MTLSizeMake(ne01, ne11, ne12) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
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@ -555,6 +607,9 @@ void ggml_metal_graph_compute(
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switch (src0->type) {
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case GGML_TYPE_F16: [encoder setComputePipelineState:ctx->pipeline_get_rows_f16]; break;
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case GGML_TYPE_Q4_0: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_0]; break;
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case GGML_TYPE_Q2_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q2_k]; break;
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case GGML_TYPE_Q4_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_k]; break;
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case GGML_TYPE_Q6_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q6_k]; break;
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default: GGML_ASSERT(false && "not implemented");
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}
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504
ggml-metal.metal
504
ggml-metal.metal
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@ -303,18 +303,37 @@ kernel void kernel_mul_mat_q4_0_f32(
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sum[ith] += acc*d;
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}
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// accumulate the sum from all threads in the threadgroup
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//
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// Accumulate the sum from all threads in the threadgroup
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// This version is slightly faster than the commented out one below,
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// which I copy-pasted from ggerganov's q4_0 dot product for metal.
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//
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threadgroup_barrier(mem_flags::mem_threadgroup);
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for (uint i = nth/2; i > 0; i /= 2) {
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if (ith < i) {
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sum[ith] += sum[ith + i];
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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if (ith%4 == 0) {
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for (int i = 1; i < 4; ++i) sum[ith] += sum[ith + i];
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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if (ith%16 == 0) {
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for (int i = 4; i < 16; i += 4) sum[ith] += sum[ith + i];
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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if (ith == 0) {
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for (int i = 16; i < nth; i += 16) sum[0] += sum[i];
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dst[r1*ne0 + r0] = sum[0];
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}
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//// accumulate the sum from all threads in the threadgroup
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//threadgroup_barrier(mem_flags::mem_threadgroup);
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//for (uint i = nth/2; i > 0; i /= 2) {
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// if (ith < i) {
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// sum[ith] += sum[ith + i];
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// }
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// threadgroup_barrier(mem_flags::mem_threadgroup);
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//}
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//if (ith == 0) {
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// dst[r1*ne0 + r0] = sum[0];
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//}
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}
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kernel void kernel_mul_mat_f16_f32(
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@ -503,3 +522,474 @@ kernel void kernel_cpy_f32_f32(
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dst_data[i00] = src[0];
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}
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}
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//============================================ k-quants ======================================================
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#define QK_K 256
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typedef struct {
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uint8_t scales[QK_K/16]; // scales and mins, quantized with 4 bits
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uint8_t qs[QK_K/4]; // quants
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half d; // super-block scale for quantized scales
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half dmin; // super-block scale for quantized mins
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} block_q2_k;
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typedef struct {
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half d; // super-block scale for quantized scales
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half dmin; // super-block scale for quantized mins
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uint8_t scales[3*QK_K/64]; // scales and mins, quantized with 6 bits
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uint8_t qs[QK_K/2]; // 4--bit quants
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} block_q4_k;
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typedef struct {
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uint8_t ql[QK_K/2]; // quants, lower 4 bits
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uint8_t qh[QK_K/4]; // quants, upper 2 bits
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int8_t scales[QK_K/16]; // scales, quantized with 8 bits
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half d; // super-block scale
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} block_q6_k;
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static inline uchar4 get_scale_min_k4(int j, device const uint8_t * q) {
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uchar4 r;
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if (j < 4) {
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r[0] = q[j+0] & 63; r[1] = q[j+4] & 63;
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r[2] = q[j+1] & 63; r[3] = q[j+5] & 63;
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} else {
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r[0] = (q[j+4] & 0xF) | ((q[j-4] >> 6) << 4);
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r[1] = (q[j+4] >> 4) | ((q[j-0] >> 6) << 4);
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r[2] = (q[j+5] & 0xF) | ((q[j-3] >> 6) << 4);
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r[3] = (q[j+5] >> 4) | ((q[j+1] >> 6) << 4);
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}
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return r;
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}
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//========================================== dequantization =============================
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static void dequantize_row_q2_k(device const block_q2_k * x, device float * y, int k) {
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assert(k % QK_K == 0);
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const int nb = k / QK_K;
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for (int i = 0; i < nb; i++) {
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const float d = x[i].d;
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const float min = x[i].dmin;
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device const uint8_t * q = x[i].qs;
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int is = 0;
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float dl, ml;
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for (int n = 0; n < QK_K; n += 128) {
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int shift = 0;
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for (int j = 0; j < 4; ++j) {
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uint8_t sc = x[i].scales[is++];
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dl = d * (sc & 0xF); ml = min * (sc >> 4);
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for (int l = 0; l < 16; ++l) *y++ = dl * ((int8_t)((q[l] >> shift) & 3)) - ml;
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sc = x[i].scales[is++];
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dl = d * (sc & 0xF); ml = min * (sc >> 4);
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for (int l = 0; l < 16; ++l) *y++ = dl * ((int8_t)((q[l+16] >> shift) & 3)) - ml;
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shift += 2;
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}
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q += 32;
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}
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}
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}
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static void dequantize_row_q4_k(device const block_q4_k * x, device float * y, int k) {
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assert(k % QK_K == 0);
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const int nb = k / QK_K;
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for (int i = 0; i < nb; i++) {
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const float d = x[i].d;
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const float min = x[i].dmin;
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device const uint8_t * q = x[i].qs;
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device const uint8_t * scales = x[i].scales;
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int is = 0;
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for (int j = 0; j < QK_K; j += 64) {
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const uchar4 sc = get_scale_min_k4(is, scales);
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const float d1 = d * sc[0]; const float m1 = min * sc[1];
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const float d2 = d * sc[2]; const float m2 = min * sc[3];
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for (int l = 0; l < 32; ++l) *y++ = d1 * (q[l] & 0xF) - m1;
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for (int l = 0; l < 32; ++l) *y++ = d2 * (q[l] >> 4) - m2;
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q += 32; is += 2;
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}
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}
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}
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static void dequantize_row_q6_k(device const block_q6_k * x, device float * y, int k) {
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assert(k % QK_K == 0);
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const int nb = k / QK_K;
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for (int i = 0; i < nb; i++) {
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device const uint8_t * ql = x[i].ql;
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device const uint8_t * qh = x[i].qh;
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device const int8_t * sc = x[i].scales;
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const float d = x[i].d;
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for (int n = 0; n < QK_K; n += 128) {
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for (int l = 0; l < 32; ++l) {
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int is = l/16;
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const int8_t q1 = (int8_t)((ql[l + 0] & 0xF) | (((qh[l] >> 0) & 3) << 4)) - 32;
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const int8_t q2 = (int8_t)((ql[l + 32] & 0xF) | (((qh[l] >> 2) & 3) << 4)) - 32;
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const int8_t q3 = (int8_t)((ql[l + 0] >> 4) | (((qh[l] >> 4) & 3) << 4)) - 32;
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const int8_t q4 = (int8_t)((ql[l + 32] >> 4) | (((qh[l] >> 6) & 3) << 4)) - 32;
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y[l + 0] = d * sc[is + 0] * q1;
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y[l + 32] = d * sc[is + 2] * q2;
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y[l + 64] = d * sc[is + 4] * q3;
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y[l + 96] = d * sc[is + 6] * q4;
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}
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y += 128;
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ql += 64;
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qh += 32;
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sc += 8;
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}
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}
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}
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kernel void kernel_get_rows_q2_k(
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device const void * src0,
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device const int * src1,
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device float * dst,
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constant int64_t & ne00,
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constant uint64_t & nb01,
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constant uint64_t & nb1,
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uint tpig[[thread_position_in_grid]]) {
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const int i = tpig;
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const int r = ((device int32_t *) src1)[i];
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dequantize_row_q2_k(
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(device const block_q2_k *) ((device char *) src0 + r*nb01),
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(device float *) ((device char *) dst + i*nb1), ne00);
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}
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kernel void kernel_get_rows_q4_k(
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device const void * src0,
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device const int * src1,
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device float * dst,
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constant int64_t & ne00,
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constant uint64_t & nb01,
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constant uint64_t & nb1,
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uint tpig[[thread_position_in_grid]]) {
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const int i = tpig;
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const int r = ((device int32_t *) src1)[i];
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dequantize_row_q4_k(
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(device const block_q4_k *) ((device char *) src0 + r*nb01),
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(device float *) ((device char *) dst + i*nb1), ne00);
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}
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kernel void kernel_get_rows_q6_k(
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device const void * src0,
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device const int * src1,
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device float * dst,
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constant int64_t & ne00,
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constant uint64_t & nb01,
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constant uint64_t & nb1,
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uint tpig[[thread_position_in_grid]]) {
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const int i = tpig;
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const int r = ((device int32_t *) src1)[i];
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dequantize_row_q6_k(
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(device const block_q6_k *) ((device char *) src0 + r*nb01),
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(device float *) ((device char *) dst + i*nb1), ne00);
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}
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//====================================== dot products =========================
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kernel void kernel_mul_mat_q2_k_f32(
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device const void * src0,
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device const float * src1,
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device float * dst,
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constant int64_t & ne00,
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constant int64_t & ne01,
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constant uint64_t & nb00,
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constant uint64_t & nb01,
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constant uint64_t & nb02,
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constant int64_t & ne10,
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constant int64_t & ne11,
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constant uint64_t & nb10,
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constant uint64_t & nb11,
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constant uint64_t & nb12,
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constant int64_t & ne0,
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constant int64_t & ne1,
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threadgroup float * sum [[threadgroup(0)]],
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uint2 tgpig[[threadgroup_position_in_grid]],
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uint2 tpig[[thread_position_in_grid]], // we don't use this for now
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uint2 tpitg[[thread_position_in_threadgroup]],
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uint2 tptg[[threads_per_threadgroup]]) {
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const int nb = ne00/QK_K;
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const int64_t r0 = tgpig.x;
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const int64_t r1 = tgpig.y;
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device const block_q2_k * x = (device const block_q2_k *) src0 + r0*nb;
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device const float * yy = (device const float *) src1 + r1*ne10;
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const int nth = tptg.x*tptg.y;
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const int ith = tptg.y*tpitg.x + tpitg.y;
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const int tid = tpitg.y; // 0...16
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const int il = tid/4; // 0...3
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const int ir = tid%4; // 0...3
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const int ip = il/2; // 0 or 1
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const int shift1 = 4*(il%2);// 0 or 4
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const int shift2 = shift1+2;// 2 or 6
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const int n = 8;
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const int is = 4*il + (n*ir)/16;
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sum[ith] = 0.0f;
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float sumf = 0;
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for (int i = tpitg.x; i < nb; i += tptg.x) {
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device const uint8_t * q = x[i].qs + 32*ip + n*ir;
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device const uint8_t * scales = x[i].scales + is;
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uint8_t d1 = scales[0] & 0xF;
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uint8_t m1 = scales[0] >> 4;
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uint8_t d2 = scales[2] & 0xF;
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uint8_t m2 = scales[2] >> 4;
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device const float * y = yy + i*QK_K + 64*il + n*ir;
|
||||
|
||||
const float dall = (float)x[i].d;
|
||||
const float dmin = (float)x[i].dmin;
|
||||
|
||||
float4 s = {0.f, 0.f, 0.f, 0.f};
|
||||
for (int l = 0; l < n; ++l) {
|
||||
s[0] += y[l+ 0] * ((q[l] >> shift1) & 3); s[1] += y[l+ 0];
|
||||
s[2] += y[l+32] * ((q[l] >> shift2) & 3); s[3] += y[l+32];
|
||||
}
|
||||
sumf += dall * (s[0] * d1 + s[2] * d2) - dmin * (s[1] * m1 + s[3] * m2);
|
||||
|
||||
|
||||
}
|
||||
sum[ith] = sumf;
|
||||
|
||||
//
|
||||
// Accumulate the sum from all threads in the threadgroup
|
||||
// This version is slightly faster than the commented out one below,
|
||||
// which I copy-pasted from ggerganov's q4_0 dot product for metal.
|
||||
//
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
if (ith%4 == 0) {
|
||||
for (int i = 1; i < 4; ++i) sum[ith] += sum[ith + i];
|
||||
}
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
if (ith%16 == 0) {
|
||||
for (int i = 4; i < 16; i += 4) sum[ith] += sum[ith + i];
|
||||
}
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
if (ith == 0) {
|
||||
for (int i = 16; i < nth; i += 16) sum[0] += sum[i];
|
||||
dst[r1*ne0 + r0] = sum[0];
|
||||
}
|
||||
|
||||
//// accumulate the sum from all threads in the threadgroup
|
||||
//threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
//for (uint i = nth/2; i > 0; i /= 2) {
|
||||
// if (ith < i) {
|
||||
// sum[ith] += sum[ith + i];
|
||||
// }
|
||||
// threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
//}
|
||||
|
||||
//if (ith == 0) {
|
||||
// dst[r1*ne0 + r0] = sum[0];
|
||||
//}
|
||||
}
|
||||
|
||||
kernel void kernel_mul_mat_q4_k_f32(
|
||||
device const void * src0,
|
||||
device const float * src1,
|
||||
device float * dst,
|
||||
constant int64_t & ne00,
|
||||
constant int64_t & ne01,
|
||||
constant uint64_t & nb00,
|
||||
constant uint64_t & nb01,
|
||||
constant uint64_t & nb02,
|
||||
constant int64_t & ne10,
|
||||
constant int64_t & ne11,
|
||||
constant uint64_t & nb10,
|
||||
constant uint64_t & nb11,
|
||||
constant uint64_t & nb12,
|
||||
constant int64_t & ne0,
|
||||
constant int64_t & ne1,
|
||||
threadgroup float * sum [[threadgroup(0)]],
|
||||
uint2 tgpig[[threadgroup_position_in_grid]],
|
||||
uint2 tpig[[thread_position_in_grid]], // we don't use this for now
|
||||
uint2 tpitg[[thread_position_in_threadgroup]],
|
||||
uint2 tptg[[threads_per_threadgroup]]) {
|
||||
|
||||
const int nb = ne00/QK_K;
|
||||
|
||||
const int64_t r0 = tgpig.x;
|
||||
const int64_t r1 = tgpig.y;
|
||||
|
||||
device const block_q4_k * x = (device const block_q4_k *) src0 + r0*nb;
|
||||
device const float * yy = (device const float *) src1 + r1*ne10;
|
||||
|
||||
const uint nth = tptg.x*tptg.y;
|
||||
const uint ith = tptg.y*tpitg.x + tpitg.y;
|
||||
|
||||
const int tid = tpitg.y; // 0...16
|
||||
const int il = tid/4; // 0...3
|
||||
const int ir = tid%4; // 0...3
|
||||
const int n = 8;
|
||||
const int is = 2*il;
|
||||
|
||||
sum[ith] = 0.0f;
|
||||
|
||||
float sumf = 0;
|
||||
for (int i = tpitg.x; i < nb; i += tptg.x) {
|
||||
|
||||
device const uint8_t * q = (x + i)->qs + 32*il + n*ir;
|
||||
device const float * y = yy + i*QK_K + 64*il + n*ir;
|
||||
device const uint8_t * scales = (x + i)->scales;
|
||||
|
||||
const float dall = (float)((x + i)->d);
|
||||
const float dmin = (float)((x + i)->dmin);
|
||||
|
||||
const uchar4 sc = get_scale_min_k4(is, scales);
|
||||
|
||||
float4 s = {0.f, 0.f, 0.f, 0.f};
|
||||
for (int l = 0; l < n; ++l) {
|
||||
s[0] += y[l+ 0] * (q[l] & 0xF); s[1] += y[l+ 0];
|
||||
s[2] += y[l+32] * (q[l] >> 4); s[3] += y[l+32];
|
||||
}
|
||||
sumf += dall * (s[0] * sc[0] + s[2] * sc[2]) - dmin * (s[1] * sc[1] + s[3] * sc[3]);
|
||||
|
||||
}
|
||||
sum[ith] = sumf;
|
||||
|
||||
//
|
||||
// Accumulate the sum from all threads in the threadgroup
|
||||
// This version is slightly faster than the commented out one below,
|
||||
// which I copy-pasted from ggerganov's q4_0 dot product for metal.
|
||||
//
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
if (ith%4 == 0) {
|
||||
for (int i = 1; i < 4; ++i) sum[ith] += sum[ith + i];
|
||||
}
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
if (ith%16 == 0) {
|
||||
for (int i = 4; i < 16; i += 4) sum[ith] += sum[ith + i];
|
||||
}
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
if (ith == 0) {
|
||||
for (int i = 16; i < nth; i += 16) sum[0] += sum[i];
|
||||
dst[r1*ne0 + r0] = sum[0];
|
||||
}
|
||||
|
||||
//// accumulate the sum from all threads in the threadgroup
|
||||
//threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
//for (uint i = nth/2; i > 0; i /= 2) {
|
||||
// if (ith < i) {
|
||||
// sum[ith] += sum[ith + i];
|
||||
// }
|
||||
// threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
//}
|
||||
|
||||
//if (ith == 0) {
|
||||
// dst[r1*ne0 + r0] = sum[0];
|
||||
//}
|
||||
}
|
||||
|
||||
kernel void kernel_mul_mat_q6_k_f32(
|
||||
device const void * src0,
|
||||
device const float * src1,
|
||||
device float * dst,
|
||||
constant int64_t & ne00,
|
||||
constant int64_t & ne01,
|
||||
constant uint64_t & nb00,
|
||||
constant uint64_t & nb01,
|
||||
constant uint64_t & nb02,
|
||||
constant int64_t & ne10,
|
||||
constant int64_t & ne11,
|
||||
constant uint64_t & nb10,
|
||||
constant uint64_t & nb11,
|
||||
constant uint64_t & nb12,
|
||||
constant int64_t & ne0,
|
||||
constant int64_t & ne1,
|
||||
threadgroup float * sum [[threadgroup(0)]],
|
||||
uint2 tgpig[[threadgroup_position_in_grid]],
|
||||
uint2 tpig[[thread_position_in_grid]], // we don't use this for now
|
||||
uint2 tpitg[[thread_position_in_threadgroup]],
|
||||
uint2 tptg[[threads_per_threadgroup]]) {
|
||||
|
||||
const uint8_t kmask1 = 0x03;
|
||||
const uint8_t kmask2 = 0x0C;
|
||||
const uint8_t kmask3 = 0x30;
|
||||
const uint8_t kmask4 = 0xC0;
|
||||
|
||||
const int nb = ne00/QK_K;
|
||||
|
||||
const int64_t r0 = tgpig.x;
|
||||
const int64_t r1 = tgpig.y;
|
||||
|
||||
device const block_q6_k * x = (device const block_q6_k *) src0 + r0*nb;
|
||||
device const float * yy = (device const float *) src1 + r1*ne10;
|
||||
|
||||
const uint nth = tptg.x*tptg.y;
|
||||
const uint ith = tptg.y*tpitg.x + tpitg.y;
|
||||
|
||||
const int step = QK_K / tptg.y; // we expect this to be 16
|
||||
const int iqs = step * tpitg.y; // 0...240 in steps of 16
|
||||
const int ip = iqs / 128; // 0 or 1
|
||||
const int il = (iqs - 128*ip)/16; // 0...7
|
||||
const int n = 4;
|
||||
const int is = 8*ip + (n*il)/16;
|
||||
|
||||
float sumf = 0;
|
||||
for (int i = tpitg.x; i < nb; i += tptg.x) {
|
||||
|
||||
device const uint8_t * ql = x[i].ql + 64*ip + n*il;
|
||||
device const uint8_t * qh = x[i].qh + 32*ip + n*il;
|
||||
device const int8_t * sc = x[i].scales + is;
|
||||
|
||||
device const float * y = yy + i * QK_K + 128*ip + n*il;
|
||||
|
||||
const float dall = x[i].d;
|
||||
|
||||
float4 sums = {0.f, 0.f, 0.f, 0.f};
|
||||
for (int l = 0; l < n; ++l) {
|
||||
sums[0] += y[l+ 0] * ((int8_t)((ql[l+ 0] & 0xF) | ((qh[l] & kmask1) << 4)) - 32);
|
||||
sums[1] += y[l+32] * ((int8_t)((ql[l+32] & 0xF) | ((qh[l] & kmask2) << 2)) - 32);
|
||||
sums[2] += y[l+64] * ((int8_t)((ql[l+ 0] >> 4) | ((qh[l] & kmask3) << 0)) - 32);
|
||||
sums[3] += y[l+96] * ((int8_t)((ql[l+32] >> 4) | ((qh[l] & kmask4) >> 2)) - 32);
|
||||
}
|
||||
|
||||
sumf += dall * (sums[0] * sc[0] + sums[1] * sc[2] + sums[2] * sc[4] + sums[3] * sc[6]);
|
||||
|
||||
}
|
||||
|
||||
sum[ith] = sumf;
|
||||
|
||||
//
|
||||
// Accumulate the sum from all threads in the threadgroup
|
||||
//
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
if (ith%4 == 0) {
|
||||
for (int i = 1; i < 4; ++i) sum[ith] += sum[ith + i];
|
||||
}
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
if (ith%16 == 0) {
|
||||
for (int i = 4; i < 16; i += 4) sum[ith] += sum[ith + i];
|
||||
}
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
if (ith == 0) {
|
||||
for (int i = 16; i < nth; i += 16) sum[0] += sum[i];
|
||||
dst[r1*ne0 + r0] = sum[0];
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
|||
22
ggml.c
22
ggml.c
|
|
@ -14729,12 +14729,12 @@ static void ggml_graph_export_leaf(const struct ggml_tensor * tensor, FILE * fou
|
|||
const int64_t * ne = tensor->ne;
|
||||
const size_t * nb = tensor->nb;
|
||||
|
||||
fprintf(fout, "%-6s %-12s %8d %8d %d %d %d %16zu %16zu %16zu %16zu %16p %32s\n",
|
||||
fprintf(fout, "%-6s %-12s %8d %" PRId64 " %" PRId64 " %" PRId64 " %" PRId64 " %16zu %16zu %16zu %16zu %16p %32s\n",
|
||||
ggml_type_name(tensor->type),
|
||||
ggml_op_name (tensor->op),
|
||||
tensor->n_dims,
|
||||
(int) ne[0], (int) ne[1], (int) ne[2], (int) ne[3],
|
||||
nb[0], nb[1], nb[2], nb[3],
|
||||
ne[0], ne[1], ne[2], ne[3],
|
||||
nb[0], nb[1], nb[2], nb[3],
|
||||
tensor->data,
|
||||
tensor->name);
|
||||
}
|
||||
|
|
@ -14743,13 +14743,13 @@ static void ggml_graph_export_node(const struct ggml_tensor * tensor, const char
|
|||
const int64_t * ne = tensor->ne;
|
||||
const size_t * nb = tensor->nb;
|
||||
|
||||
fprintf(fout, "%-6s %-6s %-12s %8d %d %d %d %d %16zu %16zu %16zu %16zu %8d %16p %32s\n",
|
||||
fprintf(fout, "%-6s %-6s %-12s %8d %" PRId64 " %" PRId64 " %" PRId64 " %" PRId64 " %16zu %16zu %16zu %16zu %8d %16p %32s\n",
|
||||
arg,
|
||||
ggml_type_name(tensor->type),
|
||||
ggml_op_name (tensor->op),
|
||||
tensor->n_dims,
|
||||
(int) ne[0], (int) ne[1], (int) ne[2], (int) ne[3],
|
||||
nb[0], nb[1], nb[2], nb[3],
|
||||
ne[0], ne[1], ne[2], ne[3],
|
||||
nb[0], nb[1], nb[2], nb[3],
|
||||
tensor->n_tasks,
|
||||
tensor->data,
|
||||
tensor->name);
|
||||
|
|
@ -14772,11 +14772,11 @@ void ggml_graph_export(const struct ggml_cgraph * cgraph, const char * fname) {
|
|||
FILE * fout = stdout;
|
||||
|
||||
fprintf(fout, "\n");
|
||||
fprintf(fout, "%-16s %8x\n", "magic", GGML_FILE_MAGIC);
|
||||
fprintf(fout, "%-16s %8d\n", "version", GGML_FILE_VERSION);
|
||||
fprintf(fout, "%-16s %8d\n", "leafs", cgraph->n_leafs);
|
||||
fprintf(fout, "%-16s %8d\n", "nodes", cgraph->n_nodes);
|
||||
fprintf(fout, "%-16s %8d\n", "eval", (int) size_eval);
|
||||
fprintf(fout, "%-16s %8x\n", "magic", GGML_FILE_MAGIC);
|
||||
fprintf(fout, "%-16s %8d\n", "version", GGML_FILE_VERSION);
|
||||
fprintf(fout, "%-16s %8d\n", "leafs", cgraph->n_leafs);
|
||||
fprintf(fout, "%-16s %8d\n", "nodes", cgraph->n_nodes);
|
||||
fprintf(fout, "%-16s %" PRIu64 "\n", "eval", size_eval);
|
||||
|
||||
// header
|
||||
fprintf(fout, "\n");
|
||||
|
|
|
|||
|
|
@ -1028,6 +1028,14 @@ static void llama_model_load_internal(
|
|||
}
|
||||
}
|
||||
|
||||
#if defined(GGML_USE_CLBLAST)
|
||||
if (file_version == LLAMA_FILE_VERSION_GGJT_V3) {
|
||||
if (hparams.ftype >= LLAMA_FTYPE_MOSTLY_Q2_K && hparams.ftype <= LLAMA_FTYPE_MOSTLY_Q6_K) {
|
||||
printf("\n===\nK-Quants are currently not supported with CLBlast.\nPlease select a q4_0, q4_0, q5_0 or q5_1 format instead.");
|
||||
}
|
||||
}
|
||||
#endif
|
||||
|
||||
if (vocab_only) {
|
||||
return;
|
||||
}
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue