Marlin 2:4 Downstream (for v0.3 release) (#239)

Support marlin 2:4 in downstream so we can have it in the release
neuralmagic · May 14, 2024 · d485d3e · d485d3e · github-actions · May 14, 2024
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diff --git a/CMakeLists.txt b/CMakeLists.txt
@@ -176,7 +176,8 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
   list(APPEND VLLM_EXT_SRC
     "csrc/quantization/aqlm/gemm_kernels.cu"
     "csrc/quantization/awq/gemm_kernels.cu"
-    "csrc/quantization/marlin/marlin_cuda_kernel.cu"
+    "csrc/quantization/marlin/dense/marlin_cuda_kernel.cu"
+    "csrc/quantization/marlin/sparse/marlin_24_cuda_kernel.cu"
     "csrc/quantization/gptq_marlin/gptq_marlin.cu"
     "csrc/quantization/gptq_marlin/gptq_marlin_repack.cu"
     "csrc/custom_all_reduce.cu")

diff --git a/csrc/ops.h b/csrc/ops.h
@@ -125,6 +125,17 @@ torch::Tensor marlin_gemm(
     int64_t size_n, 
     int64_t size_k);
 
+torch::Tensor gptq_marlin_24_gemm(
+    torch::Tensor &a, 
+    torch::Tensor &b_q_weight,
+    torch::Tensor &b_meta, 
+    torch::Tensor &b_scales,
+    torch::Tensor &workspace, 
+    int64_t num_bits,
+    int64_t size_m,
+    int64_t size_n, 
+    int64_t size_k);
+
 torch::Tensor gptq_marlin_gemm(
   torch::Tensor &a,
   torch::Tensor &b_q_weight,

diff --git a/csrc/pybind.cpp b/csrc/pybind.cpp
@@ -66,7 +66,8 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
   ops.def("aqlm_gemm", &aqlm_gemm, "Quantized GEMM for AQLM");
   ops.def("aqlm_dequant", &aqlm_dequant, "Decompression method for AQLM");
   ops.def("awq_gemm", &awq_gemm, "Quantized GEMM for AWQ");
-  ops.def("marlin_gemm", &marlin_gemm, "Marlin Optimized Quantized GEMM for GPTQ");
+  ops.def("marlin_gemm", &marlin_gemm, "Marlin (Dense) Optimized Quantized GEMM for GPTQ");
+  ops.def("gptq_marlin_24_gemm", &gptq_marlin_24_gemm, "Marlin_24 (Sparse) Optimized Quantized GEMM for GPTQ");
   ops.def("gptq_marlin_gemm", &gptq_marlin_gemm, "gptq_marlin Optimized Quantized GEMM for GPTQ");
   ops.def("gptq_marlin_repack", &gptq_marlin_repack, "gptq_marlin repack from GPTQ");
   ops.def("awq_dequantize", &awq_dequantize, "Dequantization for AWQ");

diff --git a/csrc/quantization/marlin/LICENSE → csrc/quantization/marlin/dense/LICENSE b/csrc/quantization/marlin/LICENSE → csrc/quantization/marlin/dense/LICENSE
diff --git a/...quantization/marlin/marlin_cuda_kernel.cu → ...zation/marlin/dense/marlin_cuda_kernel.cu b/...quantization/marlin/marlin_cuda_kernel.cu → ...zation/marlin/dense/marlin_cuda_kernel.cu
diff --git a/csrc/quantization/marlin/sparse/LICENSE b/csrc/quantization/marlin/sparse/LICENSE
@@ -0,0 +1,203 @@
+Contains code from https://github.com/IST-DASLab/Sparse-Marlin/
+
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diff --git a/csrc/quantization/marlin/sparse/common/base.h b/csrc/quantization/marlin/sparse/common/base.h
@@ -0,0 +1,50 @@
+/*
+ * Copyright (C) 2024 Roberto Lopez Castro (roberto.lopez.castro@udc.es). All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *       http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#pragma once
+
+namespace marlin_24 {
+
+constexpr int ceildiv(int a, int b) {
+  return (a + b - 1) / b;
+}
+
+// Instances of `Vec` are used to organize groups of >>registers<<, as needed for instance as inputs to tensor core
+// operations. Consequently, all corresponding index accesses must be compile-time constants, which is why we
+// extensively use `#pragma unroll` throughout the kernel code to guarantee this.
+template <typename T, int n>
+struct Vec {
+  T elems[n];
+  __device__ T& operator[](int i) {
+    return elems[i];
+  }
+};
+
+template<int M_, int N_, int K_> struct ShapeBase {
+    static constexpr int M = M_, N = N_, K = K_;
+};
+
+using I4 = Vec<int, 4>;
+
+// Matrix fragments for tensor core instructions; their precise layout is documented here:
+// https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#matrix-fragments-for-mma-m16n8k16-with-floating-point-type
+using FragA = Vec<half2, 4>;
+using FragB = Vec<half2, 2>;
+using FragM = Vec<uint, 1>;
+using FragC = Vec<float, 4>;
+using FragS = Vec<half2, 1>; // quantization scales
+
+}