The most common footgun with concurrent graphics/compute dispatch isn’t the async compute itself—it’s assuming separate queues mean independent execution. On GCN/RDNA hardware, graphics and compute queues still contend for the same compute units and memory subsystem, so a well-behaved compute job can silently starve your render passes or vice versa. The real hazard is implicit data hazards across queue boundaries: if a compute kernel writes to a buffer that a graphics pass reads on the next frame without an explicit pipeline barrier, you get garbage or artifacts that appear nondeterministic. Always pair each cross-queue dispatch with a synchronization primitive—semaphores in Vulkan for cross-queue signaling, or vkQueueSubmit fence sequences when you need host-side ordering. Don’t rely on the driver to infer dependencies; async compute is literally an invitation to introduce ordering bugs that don’t reproduce on your machine but crash in the field.
For debugging, stop guessing and instrument the timeline. Use GPU-Verifiable Command Buffers or RenderDoc’s GPU timing view to capture the actual execution order on the ring buffer—what you expect and what the hardware does are frequently different, especially with out-of-order execution and memory dependency resolution. A deadlock almost always traces back to a missing event/semaphore between a compute write and a graphics read, or a host-side fence being waited on before the submit that produces it. Check for the classic symptom where your app hangs with zero GPU activity: that’s a stall waiting on a
