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https://github.com/ggerganov/llama.cpp.git
synced 2024-12-29 07:34:18 +01:00
metal : assert various kernel requirements
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parent
42833bc7a8
commit
0f8df395ce
20
ggml-metal.m
20
ggml-metal.m
@ -774,8 +774,8 @@ void ggml_metal_graph_compute(
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} break;
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case GGML_OP_CONCAT:
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{
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const int64_t nb = ne00;
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int64_t nb = ne00;
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[encoder setComputePipelineState:ctx->pipeline_concat];
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[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
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[encoder setBuffer:id_src1 offset:offs_src1 atIndex:1];
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@ -807,6 +807,7 @@ void ggml_metal_graph_compute(
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[encoder setBytes:&nb length:sizeof(nb) atIndex:27];
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const int nth = MIN(1024, ne0);
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[encoder dispatchThreadgroups:MTLSizeMake(ne1, ne2, ne3) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
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} break;
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case GGML_OP_ADD:
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@ -904,9 +905,10 @@ void ggml_metal_graph_compute(
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[encoder setBuffer:id_dst offset:offs_dst atIndex:1];
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[encoder setBytes:&scale length:sizeof(scale) atIndex:2];
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const int64_t n = ggml_nelements(dst)/4;
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const int64_t n = ggml_nelements(dst);
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GGML_ASSERT(n % 4 == 0);
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[encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
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[encoder dispatchThreadgroups:MTLSizeMake(n/4, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
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} break;
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case GGML_OP_UNARY:
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switch (ggml_get_unary_op(gf->nodes[i])) {
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@ -916,9 +918,10 @@ void ggml_metal_graph_compute(
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[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
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[encoder setBuffer:id_dst offset:offs_dst atIndex:1];
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const int64_t n = ggml_nelements(dst)/4;
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const int64_t n = ggml_nelements(dst);
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GGML_ASSERT(n % 4 == 0);
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[encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
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[encoder dispatchThreadgroups:MTLSizeMake(n/4, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
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} break;
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case GGML_UNARY_OP_RELU:
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{
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@ -936,9 +939,10 @@ void ggml_metal_graph_compute(
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[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
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[encoder setBuffer:id_dst offset:offs_dst atIndex:1];
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const int64_t n = ggml_nelements(dst)/4;
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const int64_t n = ggml_nelements(dst);
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GGML_ASSERT(n % 4 == 0);
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[encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
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[encoder dispatchThreadgroups:MTLSizeMake(n/4, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
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} break;
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default:
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{
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@ -1220,6 +1224,8 @@ void ggml_metal_graph_compute(
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} break;
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case GGML_OP_RMS_NORM:
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{
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GGML_ASSERT(ne00 % 4 == 0);
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float eps;
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memcpy(&eps, dst->op_params, sizeof(float));
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@ -345,10 +345,11 @@ kernel void kernel_rms_norm(
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uint sgitg[[simdgroup_index_in_threadgroup]],
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uint tiisg[[thread_index_in_simdgroup]],
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uint ntg[[threads_per_threadgroup]]) {
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device const float4 * x = (device const float4 *) ((device const char *) src0 + tgpig*nb01);
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device const float * x_scalar = (device const float *) x;
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float4 sumf=0;
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float all_sum=0;
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device const float4 * x = (device const float4 *) ((device const char *) src0 + tgpig*nb01);
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device const float * x_scalar = (device const float *) x;
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float4 sumf = 0;
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float all_sum = 0;
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// parallel sum
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for (int i00 = tpitg; i00 < ne00/4; i00 += ntg) {
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@ -361,6 +362,7 @@ kernel void kernel_rms_norm(
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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// broadcast, simd group number is ntg / 32
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for (uint i = ntg / 32 / 2; i > 0; i /= 2) {
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if (tpitg < i) {
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@ -368,7 +370,9 @@ kernel void kernel_rms_norm(
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}
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}
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if (tpitg == 0) {
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for (int i = 4 * (ne00 / 4); i < ne00; i++) {sum[0] += x_scalar[i];}
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for (int i = 4 * (ne00 / 4); i < ne00; i++) {
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sum[0] += x_scalar[i];
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}
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sum[0] /= ne00;
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}
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@ -383,7 +387,9 @@ kernel void kernel_rms_norm(
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y[i00] = x[i00] * scale;
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}
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if (tpitg == 0) {
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for (int i00 = 4 * (ne00 / 4); i00 < ne00; i00++) {y_scalar[i00] = x_scalar[i00] * scale;}
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for (int i00 = 4 * (ne00 / 4); i00 < ne00; i00++) {
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y_scalar[i00] = x_scalar[i00] * scale;
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}
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}
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}
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