Nowadays GPUs are utilized for both graphics rendering and general-purpose compute (GPGPU). For the latter, CUDA is the indisputable leading solution.

GPGPU, ML Inference, and Vulkan Compute

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2021-08-04 12:30:14

Nowadays GPUs are utilized for both graphics rendering and general-purpose compute (GPGPU). For the latter, CUDA is the indisputable leading solution. Though, with so many other GPU vendors, the quest for a GPGPU standard never stops. OpenCL was a great attempt and is used widely; but still it falls short on many aspects. Given the success of Vulkan in graphics and it being both a graphics and compute API, one would wonder whether it can actually be the next-generation GPGPU standard. I certainly believe so; but the road is not full of roses.

Please don’t disagree yet. 😊 Generally speaking, compute can mean anything. Even for GPGPU, there are a variety of domains and applications. These are all broad and multifaceted topics; we might be thinking/talking about different aspects. So let me be more specific:

I believe Vulkan (compute) has the potential to be the next-generation GPGPU standard for various GPUs to support various domains; one immediate compelling application, though, is machine learning inference for resource-constrained scenarios like in mobile/edge devices and for gaming. Fulfilling it, Vulkan (compute) will gain further ground as a GPGPU standard and trickle down to more domains and applications.

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