GPUs make work parallelism very easy by design: each drawcall/dispatch shader instruction operates on batches of vertices, pixels, threads in general at the same time automatically. On the other hand, GPU work is pipelined, its architecture comprises various specialised (fixed function like input assembler, raster) and programmable (like Streaming Multiprocessor/SM) units connected by queues and…

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The post explores the concept of asynchronous compute within GPUs, highlighting how it enables better utilization of GPU resources by allowing tasks to run concurrently, thus improving overall performance. It discusses the importance of proper task pairing to maximize the benefits of async compute and delves into technical details including command queues, synchronization, and potential bottlenecks. The author shares insights on implementing async compute using DirectX 12 and provides examples from a toy renderer to illustrate the impact on performance.

Async compute all the things