metal : efficient flash_attn_f16 implementation
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17720fad66
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1446a12b29
3 changed files with 195 additions and 118 deletions
14
ggml-metal.m
14
ggml-metal.m
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@ -2183,6 +2183,7 @@ static bool ggml_metal_graph_compute(
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struct ggml_tensor * src3 = gf->nodes[i]->src[3];
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GGML_ASSERT(ggml_are_same_shape(src1, src2));
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GGML_ASSERT(src3);
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size_t offs_src2 = 0;
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size_t offs_src3 = 0;
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@ -2252,15 +2253,20 @@ static bool ggml_metal_graph_compute(
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[encoder setBytes:&ne3 length:sizeof( int64_t) atIndex:26];
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[encoder setBytes:&scale length:sizeof( float) atIndex:27];
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const int64_t nwarps = 32;
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const int64_t nhptg = 2; // heads per threadgroup
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// for small batches use more simdgroups (needs more tests, to confirm if it's worth it)
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const int64_t nsg = ne01 < 4 ? 4 : 2; // simdgroups per threadgroup (a.k.a. warps)
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const size_t smem = (nhptg*ne00 + nwarps*(nhptg*ne00 + 32))*(sizeof(float)/2);
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const int64_t nqptg = 8; // queries per threadgroup !! sync with kernel template arguments !!
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const int64_t ncpsg = 32; // cache values per simdgroup (does not work for other values)
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//const size_t smem = nqptg*(nhptg*ne00 + nsg*(nhptg*ne00 + 256))*(sizeof(float)/2);
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const size_t smem = nqptg*(ne00 + nsg*(ne00 + 1*ncpsg))*(sizeof(float)/2);
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//printf("smem: %zu, max: %zu\n", smem, ctx->device.maxThreadgroupMemoryLength);
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GGML_ASSERT(smem <= ctx->device.maxThreadgroupMemoryLength);
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[encoder setThreadgroupMemoryLength:smem atIndex:0];
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[encoder dispatchThreadgroups:MTLSizeMake(ne01, (ne02 + nhptg - 1)/(nhptg), ne03) threadsPerThreadgroup:MTLSizeMake(32, nwarps, 1)];
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[encoder dispatchThreadgroups:MTLSizeMake((ne01 + nqptg - 1)/nqptg, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(32, nsg, 1)];
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} break;
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case GGML_OP_DUP:
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case GGML_OP_CPY:
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