From 043f806207303586a0c903f7c1aaa208be03af97 Mon Sep 17 00:00:00 2001
From: danielhanchen <elliegouldingstuff@gmail.com>
Date: Sun, 30 Aug 2026 11:11:20 +0000
Subject: [PATCH] ggml-cuda: stop scheduling compute onto the host buffer on
 HIP integrated GPUs

Carries ggml-org/llama.cpp#25863. 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 re-enables direct
host-buffer compute on APUs, which is the path the gfx1151 corruption reports
bisect to. Pinned staging stays available; only compute directly out of the
host buffer is refused.
---
 ggml/src/ggml-cuda/ggml-cuda.cu | 35 +++++++++++++++++++++++++++++++--
 1 file changed, 33 insertions(+), 2 deletions(-)

diff --git a/ggml/src/ggml-cuda/ggml-cuda.cu b/ggml/src/ggml-cuda/ggml-cuda.cu
index 2456f7dcc62..a7db96af999 100644
--- a/ggml/src/ggml-cuda/ggml-cuda.cu
+++ b/ggml/src/ggml-cuda/ggml-cuda.cu
@@ -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;
 
@@ -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
@@ -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();
 }
 
@@ -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) {