mtgpu: disable flash attention on qy1 (MTT S80)

Signed-off-by: Xiaodong Ye <[email protected]>

Author: yeahdongcn

common/arg.cpp

@@ -703,7 +703,12 @@ gpt_params_context gpt_params_parser_init(gpt_params & params, llama_example ex,
         {"-fa", "--flash-attn"},
         format("enable Flash Attention (default: %s)", params.flash_attn ? "enabled" : "disabled"),
         [](gpt_params & params) {
+#ifdef FLASH_ATTN_AVAILABLE
             params.flash_attn = true;
+#else
+            GGML_UNUSED(params);
+            fprintf(stderr, "warning: flash attention is not supported\n");
+#endif // FLASH_ATTN_AVAILABLE
         }
     ).set_env("LLAMA_ARG_FLASH_ATTN"));
     add_opt(llama_arg(

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.