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qGPU Strengths

Last updated: 2022-11-14 18:23:39

    qGPU Strengths

    • Flexibility: Finely configure GPU computing capacity and vRAM size.
    • Strong isolation: vRAM and computing power can be strictly isolated.
    • Hybrid deployment: Supports online and offline hybrid deployment to maximize the GPU utilization.
    • Coverage: Supports popular architectures including Volta (such as V100), Turing (such as T4) and Ampere (such as A100 and A10).
    • Cloud nativeness: Standard Kubernetes and NVIDIA Docker solutions are supported.
    • Compatibility: No need to rewrite application code or replace CUDA libraries, and it is easily deployed in a way imperceptible to the application.
    • High performance: Virtualization is applied at the underlying layer of GPU devices, realizing efficient convergence and nearly zero loss of throughput.
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