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ggml-cuda: stop scheduling compute onto the host buffer on HIP integrated GPUs #145

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ggml-cuda: stop scheduling compute onto the host buffer on HIP integrated GPUs #145

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35 changes: 33 additions & 2 deletions ggml/src/ggml-cuda/ggml-cuda.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -4822,6 +4822,30 @@ static enum ggml_backend_dev_type ggml_backend_cuda_device_get_type(ggml_backend
: GGML_BACKEND_DEVICE_TYPE_GPU;
}

static bool ggml_backend_cuda_host_buffer_supported() {
return getenv("GGML_CUDA_NO_PINNED") == nullptr;
}

// Whether the scheduler may place a COMPUTE input on the pinned host buffer type.
//
// On HIP the device info sets `integrated = prop.integrated`, while the CUDA
// branch of the same #if keeps it false "due to issues with corrupted output".
// That asymmetry is what re-enabled direct host-buffer compute on APUs, and it
// is the path several gfx1151 corruption reports bisect to. Staging through
// pinned host memory stays available; only compute directly out of it is
// refused, which is the narrowest change that closes the reports.
static bool ggml_backend_cuda_device_supports_cuda_host_buft(int device) {
#if defined(GGML_USE_HIP)
if (ggml_cuda_info().devices[device].integrated) {
return false;
}
#else
GGML_UNUSED(device);
#endif

return ggml_backend_cuda_host_buffer_supported();
}

static void ggml_backend_cuda_device_get_props(ggml_backend_dev_t dev, ggml_backend_dev_props * props) {
ggml_backend_cuda_device_context * ctx = (ggml_backend_cuda_device_context *)dev->context;

Expand All @@ -4831,7 +4855,7 @@ static void ggml_backend_cuda_device_get_props(ggml_backend_dev_t dev, ggml_back
props->device_id = ctx->pci_bus_id.empty() ? nullptr : ctx->pci_bus_id.c_str();
ggml_backend_cuda_device_get_memory(dev, &props->memory_free, &props->memory_total);

bool host_buffer = getenv("GGML_CUDA_NO_PINNED") == nullptr;
bool host_buffer = ggml_backend_cuda_host_buffer_supported();
#ifdef GGML_CUDA_NO_PEER_COPY
bool events = false;
#else
Expand Down Expand Up @@ -4860,6 +4884,10 @@ static ggml_backend_buffer_type_t ggml_backend_cuda_device_get_buffer_type(ggml_

static ggml_backend_buffer_type_t ggml_backend_cuda_device_get_host_buffer_type(ggml_backend_dev_t dev) {
GGML_UNUSED(dev);
if (!ggml_backend_cuda_host_buffer_supported()) {
return nullptr;
}

return ggml_backend_cuda_host_buffer_type();
}

Expand Down Expand Up @@ -5320,7 +5348,10 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g
static bool ggml_backend_cuda_device_supports_buft(ggml_backend_dev_t dev, ggml_backend_buffer_type_t buft) {
ggml_backend_cuda_device_context * dev_ctx = (ggml_backend_cuda_device_context *) dev->context;
const bool integrated = ggml_cuda_info().devices[dev_ctx->device].integrated;
return (ggml_backend_buft_is_cuda(buft) && buft->device == dev) || (integrated && ggml_backend_buft_is_cuda_host(buft));
return (ggml_backend_buft_is_cuda(buft) && buft->device == dev) ||
(integrated &&
ggml_backend_buft_is_cuda_host(buft) &&
ggml_backend_cuda_device_supports_cuda_host_buft(dev_ctx->device));
}

static int64_t get_op_batch_size(const ggml_tensor * op) {
Expand Down