Update ggml-cuda/mmvq.cu

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

.github/workflows/build.yml

@@ -459,7 +459,7 @@ jobs:
           path: build/bin/${{ matrix.build }}
 
   windows-cublas:
-    runs-on: windows-2019
+    runs-on: windows-latest
 
     strategy:
       matrix:

Makefile

@@ -297,10 +297,10 @@ ggml-cuda/%.o: ggml-cuda/%.cu ggml-cuda/%.cuh ggml.h ggml-common.h ggml-cuda/com
 
 ggml-cuda.o: ggml-cuda.cu ggml-cuda.h ggml.h ggml-backend.h ggml-backend-impl.h ggml-common.h $(wildcard ggml-cuda/*.cuh)
 	$(NVCC) $(NVCCFLAGS) $(CXXFLAGS) -Wno-pedantic -c $< -o $@
+endif
 
 whisper-mel-cuda.o: whisper-mel-cuda.cu whisper.h ggml.h ggml-backend.h whisper-mel.hpp whisper-mel-cuda.hpp
 	$(NVCC) $(NVCCFLAGS) $(CXXFLAGS) -Wno-pedantic -c $< -o $@
-endif
 
 ifdef WHISPER_HIPBLAS
 	ROCM_PATH   ?= /opt/rocm

whisper-mel-cuda.cu

@@ -203,14 +203,14 @@ public:
         // create Hann window
         {
             auto hw = whisper_mel_calc::hann_window();
-            CUDA_CHECK(cudaMalloc(&m_hann_window, hw.len * sizeof(float)));
+            CUDA_CHECK(cudaMallocAsync(&m_hann_window, hw.len * sizeof(float), m_stream));
             CUDA_CHECK(cudaMemcpyAsync(m_hann_window, hw.data, hw.len * sizeof(float), cudaMemcpyHostToDevice, m_stream));
         }
 
         // fill filters
         {
             auto& f = filters.data;
-            CUDA_CHECK(cudaMalloc(&m_filters, f.size() * sizeof(float)));
+            CUDA_CHECK(cudaMallocAsync(&m_filters, f.size() * sizeof(float), m_stream));
             CUDA_CHECK(cudaMemcpyAsync(m_filters, f.data(), f.size() * sizeof(float), cudaMemcpyHostToDevice, m_stream));
         }
 
@@ -243,7 +243,7 @@ public:
                 m_cufft_workspace = nullptr;
             }
             CUFFT_CHECK(cufftEstimate1d(WHISPER_N_FFT, CUFFT_R2C, max_frames, &m_cufft_workspace_size));
-            CUDA_CHECK(cudaMalloc(&m_cufft_workspace, m_cufft_workspace_size));
+            CUDA_CHECK(cudaMallocAsync(&m_cufft_workspace, m_cufft_workspace_size, m_stream));
         }
 
         // device reduce working area
@@ -261,7 +261,7 @@ public:
             cub::DeviceReduce::Max(nullptr, nbytes, temp, temp, max_frames * max_mels);
             m_log_mel_temp_storage_size = nbytes + LOG_MEL_PREFIX_SIZE;
 
-            CUDA_CHECK(cudaMalloc(&m_log_mel_temp_storage, m_log_mel_temp_storage_size));
+            CUDA_CHECK(cudaMallocAsync(&m_log_mel_temp_storage, m_log_mel_temp_storage_size, m_stream));
         }
 
         m_n_max_samples = n_samples;
@@ -286,16 +286,16 @@ public:
         const auto n_frames = 1 + (padded_samples.size() - WHISPER_N_FFT) / WHISPER_HOP_LENGTH;
 
         float * cu_padded_samples = nullptr;
-        CUDA_CHECK(cudaMalloc(&cu_padded_samples, padded_samples.size() * sizeof(float)));
+        CUDA_CHECK(cudaMallocAsync(&cu_padded_samples, padded_samples.size() * sizeof(float), m_stream));
         CUDA_CHECK(cudaMemcpyAsync(cu_padded_samples, padded_samples.data(), padded_samples.size() * sizeof(float), cudaMemcpyHostToDevice, m_stream));
 
         float * stft_in = nullptr; // contiguous buffer for stft input
-        CUDA_CHECK(cudaMalloc(&stft_in, n_frames * WHISPER_N_FFT * sizeof(float)));
+        CUDA_CHECK(cudaMallocAsync(&stft_in, n_frames * WHISPER_N_FFT * sizeof(float), m_stream));
 
         fill_stft_input(cu_padded_samples, int(n_frames), m_hann_window, stft_in, m_stream);
 
         cufftComplex* stft_out;
-        CUDA_CHECK(cudaMalloc(&stft_out, n_frames * WHISPER_N_FFT_HALF * sizeof(cufftComplex)));
+        CUDA_CHECK(cudaMallocAsync(&stft_out, n_frames * WHISPER_N_FFT_HALF * sizeof(cufftComplex), m_stream));
 
         cufftHandle plan;
         CUFFT_CHECK(cufftCreate(&plan));
@@ -311,11 +311,11 @@ public:
 
         const auto n_mag_frames = n_frames - 1; // drop last frame
         float * magnitudes;
-        CUDA_CHECK(cudaMalloc(&magnitudes, n_mag_frames * WHISPER_N_FFT_HALF * sizeof(float)));
+        CUDA_CHECK(cudaMallocAsync(&magnitudes, n_mag_frames * WHISPER_N_FFT_HALF * sizeof(float), m_stream));
         calc_magnitudes(stft_out, int(n_mag_frames), magnitudes, m_stream);
 
         float * mel_data = nullptr;
-        CUDA_CHECK(cudaMalloc(&mel_data, m_n_mel * n_mag_frames * sizeof(float)));
+        CUDA_CHECK(cudaMallocAsync(&mel_data, m_n_mel * n_mag_frames * sizeof(float), m_stream));
 
         const float fone = 1.0f, fzero = 0.0f;
         CUBLAS_CHECK(cublasSgemm(m_cublas_handle, CUBLAS_OP_T, CUBLAS_OP_N,
@@ -343,11 +343,11 @@ public:
 
         // cleanup
         CUFFT_CHECK(cufftDestroy(plan));
-        CUDA_CHECK(cudaFree(mel_data));
+        CUDA_CHECK(cudaFreeAsync(mel_data, m_stream));
-        CUDA_CHECK(cudaFree(magnitudes));
+        CUDA_CHECK(cudaFreeAsync(magnitudes, m_stream));
-        CUDA_CHECK(cudaFree(stft_out));
+        CUDA_CHECK(cudaFreeAsync(stft_out, m_stream));
-        CUDA_CHECK(cudaFree(stft_in));
+        CUDA_CHECK(cudaFreeAsync(stft_in, m_stream));
-        CUDA_CHECK(cudaFree(cu_padded_samples));
+        CUDA_CHECK(cudaFreeAsync(cu_padded_samples, m_stream));
 
         return ret;
     }

whisper.cpp

@@ -3167,7 +3167,7 @@ struct mel_calc_cpu : public whisper_mel_calc {
 }
 
 whisper_mel_calc * whisper_mel_calc_create(ggml_backend_t backend, const whisper_filters & filters) {
-#if defined(GGML_USE_CUDA) && !defined(GGML_USE_HIPBLAS)
+#if GGML_USE_CUDA
     if (ggml_backend_is_cuda(backend)) {
         auto ret = whisper_mel_calc_create_cuda(backend, filters);
         // run a warmup to avoid the first kernel launch overhead (thus we get the best perf even on the first run)