Merge df79623dc8 into 41f477879f

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

Makefile

@@ -611,7 +611,7 @@ ifdef GGML_CUDA
 
 		MK_CPPFLAGS  += -DGGML_USE_CUDA -I$(CUDA_PATH)/include
 		MK_LDFLAGS   += -lmusa -lmublas -lmusart -lpthread -ldl -lrt -L$(CUDA_PATH)/lib -L/usr/lib64
-		MK_NVCCFLAGS += -x musa -mtgpu --cuda-gpu-arch=mp_22
+		MK_NVCCFLAGS += -x musa -mtgpu --cuda-gpu-arch=mp_21 --cuda-gpu-arch=mp_22
 	else
 		ifneq ('', '$(wildcard /opt/cuda)')
 			CUDA_PATH ?= /opt/cuda

ggml/src/CMakeLists.txt

@@ -364,7 +364,7 @@ if (GGML_CUDA)
         if (GGML_MUSA)
             set_source_files_properties(${GGML_SOURCES_CUDA} PROPERTIES LANGUAGE CXX)
             foreach(SOURCE ${GGML_SOURCES_CUDA})
-                set_property(SOURCE ${SOURCE} PROPERTY COMPILE_FLAGS "-x musa -mtgpu --cuda-gpu-arch=mp_22")
+                set_property(SOURCE ${SOURCE} PROPERTY COMPILE_FLAGS "-x musa -mtgpu --cuda-gpu-arch=mp_21 --cuda-gpu-arch=mp_22")
             endforeach()
         endif()
 

ggml/src/ggml-cuda.cu

@@ -186,7 +186,7 @@ static ggml_cuda_device_info ggml_cuda_init() {
     for (int id = 0; id < info.device_count; ++id) {
         int device_vmm = 0;
 
-#if !defined(GGML_USE_HIPBLAS) && !defined(GGML_CUDA_NO_VMM) && !defined(GGML_USE_MUSA)
+#if !defined(GGML_USE_HIPBLAS) && !defined(GGML_CUDA_NO_VMM)
         CUdevice device;
         CU_CHECK(cuDeviceGet(&device, id));
         CU_CHECK(cuDeviceGetAttribute(&device_vmm, CU_DEVICE_ATTRIBUTE_VIRTUAL_MEMORY_MANAGEMENT_SUPPORTED, device));
@@ -198,7 +198,7 @@ static ggml_cuda_device_info ggml_cuda_init() {
             alloc_prop.location.id = id;
             CU_CHECK(cuMemGetAllocationGranularity(&info.devices[id].vmm_granularity, &alloc_prop, CU_MEM_ALLOC_GRANULARITY_RECOMMENDED));
         }
-#endif // !defined(GGML_USE_HIPBLAS) && !defined(GGML_CUDA_NO_VMM) && !defined(GGML_USE_MUSA)
+#endif // !defined(GGML_USE_HIPBLAS) && !defined(GGML_CUDA_NO_VMM)
         info.devices[id].vmm = !!device_vmm;
 
         cudaDeviceProp prop;
@@ -2822,6 +2822,12 @@ GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, cons
                 if (op->op == GGML_OP_MUL_MAT && a->ne[3] != b->ne[3]) {
                     return false;
                 }
+#ifdef GGML_USE_MUSA
+                if (b->type == GGML_TYPE_F16 && b->ne[2]*b->ne[3] > 1 &&
+                    !ggml_is_transposed(a) && !ggml_is_transposed(b)) {
+                    return false;
+                }
+#endif // GGML_USE_MUSA
                 switch (a->type) {
                     case GGML_TYPE_F32:
                     case GGML_TYPE_F16:
@@ -2845,6 +2851,11 @@ GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, cons
                     case GGML_TYPE_IQ3_XXS:
                     case GGML_TYPE_IQ4_NL:
                     case GGML_TYPE_IQ4_XS:
+#ifdef GGML_USE_MUSA
+                        if (a->type == GGML_TYPE_Q3_K) {
+                            return false;
+                        }
+#endif // GGML_USE_MUSA
                         return true;
                     default:
                         return false;
@@ -2969,6 +2980,9 @@ GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, cons
         case GGML_OP_LEAKY_RELU:
             return true;
         case GGML_OP_FLASH_ATTN_EXT:
+#ifndef FLASH_ATTN_AVAILABLE
+            return false;
+#endif
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
             return (op->src[0]->ne[0] == 64 && op->src[1]->type == GGML_TYPE_F16) || op->src[0]->ne[0] == 128;
 #else

ggml/src/ggml-cuda/common.cuh

@@ -50,6 +50,8 @@
 #define CC_RDNA1      (CC_OFFSET_AMD + 1010)
 #define CC_RDNA2      (CC_OFFSET_AMD + 1030)
 #define CC_RDNA3      (CC_OFFSET_AMD + 1100)
+#define CC_QY1        210
+#define CC_QY2        220
 
 #define MATRIX_ROW_PADDING 512 // last row of quant. matrices is a multiple of this to avoid out-of-bounds memory accesses
 
@@ -134,6 +136,10 @@ typedef float2 dfloat2;
 #define INT8_MMA_AVAILABLE
 #endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= CC_TURING
 
+#if !(defined(GGML_USE_MUSA) && __MUSA_ARCH__ <= CC_QY1)
+#define FLASH_ATTN_AVAILABLE
+#endif // !(defined(GGML_USE_MUSA) && __MUSA_ARCH__ <= CC_QY1)
+
 static constexpr bool fast_fp16_available(const int cc) {
     return cc >= CC_PASCAL && cc != 610;
 }

ggml/src/ggml-cuda/fattn-tile-f32.cu

@@ -44,13 +44,17 @@ static __global__ void flash_attn_tile_ext_f32(
         const int ne1,
         const int ne2,
         const int ne3) {
+#ifndef FLASH_ATTN_AVAILABLE
+    NO_DEVICE_CODE;
+    return;
+#endif // FLASH_ATTN_AVAILABLE
     // Skip unused kernel variants for faster compilation:
     if (use_logit_softcap && !(D == 128 || D == 256)) {
         NO_DEVICE_CODE;
         return;
     }
 
-    //In this kernel Q, K, V are matrices while i, j, k are matrix indices.
+    // In this kernel Q, K, V are matrices while i, j, k are matrix indices.
 
     const int ic0 = (blockIdx.x / parallel_blocks) * ncols; // Index of the Q/QKV column to work on.
     const int ip  =  blockIdx.x % parallel_blocks; // Index in group of blocks running for the same column in parallel.