Looking for advice on Asynchronous Compute and Concurrent Graphics/Compute Pipeline Dispatch – any experienced users?

[Grace Walker]

Hey everyone,

I’ve been looking into Asynchronous Compute and Concurrent Graphics/Compute Pipeline Dispatch recently and wanted to ask the community for real-world impressions.

GPU Pipeline Stages Shader Core Architecture Memory Bandwidth Allocation Hardware Preemption Semaphore Synchronization L2 Cache Organization Command Processor Compute Shader Rasterization Frame Time Variance Esports Latency Optimization Power‑Performance Tradeoff VRAM Subsystem Pipeline Bubble Elimination Context Switch Overhead

Has anyone tested this setup or experienced something similar? Any tips would be appreciated!

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[Lily Adams]

Hey man,

I dealt with this recently. The core issue usually comes down to:

The concept traces back to the early 2000s with the introduction of hardware‑based job queues in GPUs such as NVIDIA’s Tesla (2006) and AMD’s TeraScale architectures, which allowed limited concurrent kernel execution but suffered from coarse granularity and high context‑switch overhead (≈ 5–10 µs). The first true asynchronous compute capability appeared with AMD’s Graphics Core Next (GCN) 1.0 (2012), featuring multiple Asynchronous Compute Engine

Best way forward is:
Scenario 1 – Valorant (Competitive FPS) Valorant’s rendering pipeline employs a deferred shading pass followed by a temporal anti‑aliasing (TAA) resolve. The development team offloaded the TAA resolve and dynamic bloom generation to asynchronous compute waves dispatched via ACE 0 while the graphics pipeline was executing the pixel shader pass for the next frame. Measurements on an RTX 3080 showed a reduction in average frame time from 16.7 ms (60

Hope this helps!

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📍 Melbourne (Australia)

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