update for fp8

Signed-off-by: yewentao256 <zhyanwentao@126.com>

csrc/quantization/w8a8/fp8/common.cuh

@@ -0,0 +1,58 @@
+#pragma once
+
+#include "quantization/vectorization.cuh"
+#include "quantization/utils.cuh"
+
+#include <cmath>
+
+#ifdef USE_ROCM
+  #include "amd/quant_utils.cuh"
+#endif
+
+// Determines the preferred FP8 type for the current platform.
+// Note that for CUDA this just returns true,
+// but on ROCm it will check device props.
+static bool is_fp8_ocp() {
+#ifndef USE_ROCM
+  return true;
+#else
+  auto dprops = at::cuda::getCurrentDeviceProperties();
+  std::string device_arch = dprops->gcnArchName;
+  size_t substring = device_arch.find("gfx94");
+  return substring == std::string::npos;
+#endif
+}
+
+namespace vllm {
+
+__device__ __forceinline__ float atomicMaxFloat(float* addr, float value) {
+  float old;
+  old = (value >= 0)
+            ? __int_as_float(atomicMax((int*)addr, __float_as_int(value)))
+            : __uint_as_float(
+                  atomicMin((unsigned int*)addr, __float_as_uint(value)));
+
+  return old;
+}
+
+template <bool is_scale_inverted, typename fp8_type>
+__device__ __forceinline__ fp8_type scaled_fp8_conversion(float const val,
+                                                          float const scale) {
+  float x = 0.0f;
+  if constexpr (is_scale_inverted) {
+    x = val * scale;
+  } else {
+    x = val / scale;
+  }
+
+  float r =
+      fmaxf(-quant_type_max_v<fp8_type>, fminf(x, quant_type_max_v<fp8_type>));
+#ifndef USE_ROCM
+  return static_cast<fp8_type>(r);
+#else
+  // Use hardware cvt instruction for fp8 on rocm
+  return fp8::cvt_c10<fp8_type>(r);
+#endif
+}
+
+}  // namespace vllm