[Kernel] Update Cutlass int8 kernel configs for SM90 (vllm-project#5514)

Co-authored-by: Varun Sundar Rabindranath <varun@neuralmagic.com>

Author: 2 people

csrc/quantization/cutlass_w8a8/scaled_mm_c3x.cu

@@ -234,38 +234,39 @@ void cutlass_gemm_caller(torch::Tensor& out, torch::Tensor const& a,
 }
 
 template <typename InType, typename OutType,
-          template <typename, typename, typename> typename Epilogue, int32_t M>
-struct sm90_fp8_config {
+          template <typename, typename, typename> typename Epilogue>
+struct sm90_fp8_config_default {
+  // M in (128, inf)
   static_assert(std::is_same<InType, cutlass::float_e4m3_t>());
   using KernelSchedule =
       cutlass::gemm::KernelTmaWarpSpecializedPingpongFP8FastAccum;
   using EpilogueSchedule = typename cutlass::epilogue::TmaWarpSpecialized;
   using TileShape = Shape<_128, _128, _128>;
   using ClusterShape = Shape<_2, _1, _1>;
-
   using Cutlass3xGemm =
       cutlass_3x_gemm<InType, OutType, Epilogue, TileShape, ClusterShape,
                       KernelSchedule, EpilogueSchedule>;
 };
 
 template <typename InType, typename OutType,
           template <typename, typename, typename> typename Epilogue>
-struct sm90_fp8_config<InType, OutType, Epilogue, 128> {
+struct sm90_fp8_config_M128 {
+  // M in (64, 128]
   static_assert(std::is_same<InType, cutlass::float_e4m3_t>());
   using KernelSchedule =
       cutlass::gemm::KernelTmaWarpSpecializedPingpongFP8FastAccum;
   using EpilogueSchedule = typename cutlass::epilogue::TmaWarpSpecialized;
   using TileShape = Shape<_64, _128, _128>;
   using ClusterShape = Shape<_2, _1, _1>;
-
   using Cutlass3xGemm =
       cutlass_3x_gemm<InType, OutType, Epilogue, TileShape, ClusterShape,
                       KernelSchedule, EpilogueSchedule>;
 };
 
 template <typename InType, typename OutType,
           template <typename, typename, typename> typename Epilogue>
-struct sm90_fp8_config<InType, OutType, Epilogue, 64> {
+struct sm90_fp8_config_M64 {
+  // M in [1, 64]
   static_assert(std::is_same<InType, cutlass::float_e4m3_t>());
   using KernelSchedule =
       cutlass::gemm::KernelTmaWarpSpecializedPingpongFP8FastAccum;
@@ -278,6 +279,78 @@ struct sm90_fp8_config<InType, OutType, Epilogue, 64> {
                       KernelSchedule, EpilogueSchedule>;
 };
 
+template <typename InType, typename OutType,
+          template <typename, typename, typename> typename Epilogue>
+struct sm90_int8_config_default {
+  // For M > 128 and any N
+  static_assert(std::is_same<InType, int8_t>());
+  using KernelSchedule =
+      typename cutlass::gemm::KernelTmaWarpSpecializedPingpong;
+  using EpilogueSchedule = typename cutlass::epilogue::TmaWarpSpecialized;
+  using TileShape = Shape<_128, _128, _128>;
+  using ClusterShape = Shape<_2, _1, _1>;
+  using Cutlass3xGemm =
+      cutlass_3x_gemm<InType, OutType, Epilogue, TileShape, ClusterShape,
+                      KernelSchedule, EpilogueSchedule>;
+};
+
+template <typename InType, typename OutType,
+          template <typename, typename, typename> typename Epilogue>
+struct sm90_int8_config_M128 {
+  // For M in (64, 128] and any N
+  static_assert(std::is_same<InType, int8_t>());
+  using KernelSchedule =
+      typename cutlass::gemm::KernelTmaWarpSpecializedPingpong;
+  using EpilogueSchedule = typename cutlass::epilogue::TmaWarpSpecialized;
+  using TileShape = Shape<_64, _128, _128>;
+  using ClusterShape = Shape<_2, _1, _1>;
+  using Cutlass3xGemm =
+      cutlass_3x_gemm<InType, OutType, Epilogue, TileShape, ClusterShape,
+                      KernelSchedule, EpilogueSchedule>;
+};
+
+template <typename InType, typename OutType,
+          template <typename, typename, typename> typename Epilogue>
+struct sm90_int8_config_M64 {
+  // For M in (32, 64] and any N
+  static_assert(std::is_same<InType, int8_t>());
+  using KernelSchedule = typename cutlass::gemm::KernelTmaWarpSpecialized;
+  using EpilogueSchedule = typename cutlass::epilogue::TmaWarpSpecialized;
+  using TileShape = Shape<_64, _64, _256>;
+  using ClusterShape = Shape<_1, _1, _1>;
+  using Cutlass3xGemm =
+      cutlass_3x_gemm<InType, OutType, Epilogue, TileShape, ClusterShape,
+                      KernelSchedule, EpilogueSchedule>;
+};
+
+template <typename InType, typename OutType,
+          template <typename, typename, typename> typename Epilogue>
+struct sm90_int8_config_M32_NBig {
+  // For M in [1, 32] and N >= 8192
+  static_assert(std::is_same<InType, int8_t>());
+  using KernelSchedule = typename cutlass::gemm::KernelTmaWarpSpecialized;
+  using EpilogueSchedule = typename cutlass::epilogue::TmaWarpSpecialized;
+  using TileShape = Shape<_64, _128, _256>;
+  using ClusterShape = Shape<_1, _4, _1>;
+  using Cutlass3xGemm =
+      cutlass_3x_gemm<InType, OutType, Epilogue, TileShape, ClusterShape,
+                      KernelSchedule, EpilogueSchedule>;
+};
+
+template <typename InType, typename OutType,
+          template <typename, typename, typename> typename Epilogue>
+struct sm90_int8_config_M32_NSmall {
+  // For M in [1, 32] and N < 8192
+  static_assert(std::is_same<InType, int8_t>());
+  using KernelSchedule = typename cutlass::gemm::KernelTmaWarpSpecialized;
+  using EpilogueSchedule = typename cutlass::epilogue::TmaWarpSpecialized;
+  using TileShape = Shape<_64, _64, _256>;
+  using ClusterShape = Shape<_1, _8, _1>;
+  using Cutlass3xGemm =
+      cutlass_3x_gemm<InType, OutType, Epilogue, TileShape, ClusterShape,
+                      KernelSchedule, EpilogueSchedule>;
+};
+
 }  // namespace
 
 template <typename InType, typename OutType,
@@ -291,11 +364,12 @@ void cutlass_gemm_sm90_fp8_dispatch(torch::Tensor& out, torch::Tensor const& a,
   TORCH_CHECK(b.dtype() == torch::kFloat8_e4m3fn);
 
   using Cutlass3xGemmDefault =
-      typename sm90_fp8_config<InType, OutType, Epilogue, 0>::Cutlass3xGemm;
+      typename sm90_fp8_config_default<InType, OutType,
+                                       Epilogue>::Cutlass3xGemm;
   using Cutlass3xGemmM64 =
-      typename sm90_fp8_config<InType, OutType, Epilogue, 64>::Cutlass3xGemm;
+      typename sm90_fp8_config_M64<InType, OutType, Epilogue>::Cutlass3xGemm;
   using Cutlass3xGemmM128 =
-      typename sm90_fp8_config<InType, OutType, Epilogue, 128>::Cutlass3xGemm;
+      typename sm90_fp8_config_M128<InType, OutType, Epilogue>::Cutlass3xGemm;
 
   uint32_t const m = a.size(0);
   uint32_t const mp2 =
@@ -316,6 +390,61 @@ void cutlass_gemm_sm90_fp8_dispatch(torch::Tensor& out, torch::Tensor const& a,
   }
 }
 
+template <typename InType, typename OutType,
+          template <typename, typename, typename> typename Epilogue,
+          typename... EpilogueArgs>
+void cutlass_gemm_sm90_int8_dispatch(torch::Tensor& out, torch::Tensor const& a,
+                                     torch::Tensor const& b,
+                                     EpilogueArgs&&... args) {
+  static_assert(std::is_same<InType, int8_t>());
+  TORCH_CHECK(a.dtype() == torch::kInt8);
+  TORCH_CHECK(b.dtype() == torch::kInt8);
+
+  using Cutlass3xGemmDefault =
+      typename sm90_int8_config_default<InType, OutType,
+                                        Epilogue>::Cutlass3xGemm;
+  using Cutlass3xGemmM128 =
+      typename sm90_int8_config_M128<InType, OutType, Epilogue>::Cutlass3xGemm;
+  using Cutlass3xGemmM64 =
+      typename sm90_int8_config_M64<InType, OutType, Epilogue>::Cutlass3xGemm;
+  using Cutlass3xGemmM32NBig =
+      typename sm90_int8_config_M32_NBig<InType, OutType,
+                                         Epilogue>::Cutlass3xGemm;
+  using Cutlass3xGemmM32NSmall =
+      typename sm90_int8_config_M32_NSmall<InType, OutType,
+                                           Epilogue>::Cutlass3xGemm;
+
+  uint32_t const n = out.size(1);
+  bool const is_small_n = n < 8192;
+
+  uint32_t const m = a.size(0);
+  uint32_t const mp2 =
+      std::max(static_cast<uint32_t>(32), next_pow_2(m));  // next power of 2
+
+  if (mp2 <= 32) {
+    // m in [1, 32]
+    if (is_small_n) {
+      return cutlass_gemm_caller<Cutlass3xGemmM32NSmall>(
+          out, a, b, std::forward<EpilogueArgs>(args)...);
+    } else {
+      return cutlass_gemm_caller<Cutlass3xGemmM32NBig>(
+          out, a, b, std::forward<EpilogueArgs>(args)...);
+    }
+  } else if (mp2 <= 64) {
+    // m in (32, 64]
+    return cutlass_gemm_caller<Cutlass3xGemmM64>(
+        out, a, b, std::forward<EpilogueArgs>(args)...);
+  } else if (mp2 <= 128) {
+    // m in (64, 128]
+    return cutlass_gemm_caller<Cutlass3xGemmM128>(
+        out, a, b, std::forward<EpilogueArgs>(args)...);
+  } else {
+    // m in (128, inf)
+    return cutlass_gemm_caller<Cutlass3xGemmDefault>(
+        out, a, b, std::forward<EpilogueArgs>(args)...);
+  }
+}
+
 void cutlass_scaled_mm_sm90(torch::Tensor& out, torch::Tensor const& a,
                             torch::Tensor const& b,
                             torch::Tensor const& a_scales,
@@ -326,22 +455,14 @@ void cutlass_scaled_mm_sm90(torch::Tensor& out, torch::Tensor const& a,
   if (a.dtype() == torch::kInt8) {
     TORCH_CHECK(b.dtype() == torch::kInt8);
 
-    using TileShape = Shape<_128, _128, _128>;
-    using ClusterShape = Shape<_1, _2, _1>;
-    using KernelSchedule =
-        typename cutlass::gemm::KernelTmaWarpSpecializedPingpong;
-    using EpilogueSchedule = typename cutlass::epilogue::TmaWarpSpecialized;
-
     if (out.dtype() == torch::kBFloat16) {
-      return cutlass_gemm_caller<cutlass_3x_gemm<
-          int8_t, cutlass::bfloat16_t, ScaledEpilogue, TileShape, ClusterShape,
-          KernelSchedule, EpilogueSchedule>>(out, a, b, a_scales, b_scales);
+      return cutlass_gemm_sm90_int8_dispatch<int8_t, cutlass::bfloat16_t,
+                                             ScaledEpilogue>(
+          out, a, b, a_scales, b_scales);
     } else {
       TORCH_CHECK(out.dtype() == torch::kFloat16);
-
-      return cutlass_gemm_caller<
-          cutlass_3x_gemm<int8_t, cutlass::half_t, ScaledEpilogue, TileShape,
-                          ClusterShape, KernelSchedule, EpilogueSchedule>>(
+      return cutlass_gemm_sm90_int8_dispatch<int8_t, cutlass::half_t,
+                                             ScaledEpilogue>(
           out, a, b, a_scales, b_scales);
     }
   } else {