In addition, 23 of the top 25 systems in the Green500, which screens the most energy-efficient systems, are powered by NVIDIA technology. On average, Nvidia GPU-based supercomputers are 3.5 times more energy efficient than a non-GPU Green500 system.
Microsoft’s GPU-accelerated Azure supercomputer entered the top 10, becoming the first cloud-based system to enter the top 10. AI is revolutionizing computing for scientific research. Recently, the number of papers using high-performance computing (HPC) and machine learning has rapidly increased, and the number of related papers submitted from about 600 papers in 2018 increased to 5,000 papers in 2020.
HPL-AI is a convergence of HPC and AI workloads that use mixed-precision arithmetic (the basis of deep learning and various scientific research and commercial applications) while still providing the full accuracy of double-precision arithmetic (which serves as a standard measurer for traditional HPC benchmarks). It’s a new benchmark.
MLPerf HPC evaluates computing styles that accelerate and improve simulations on supercomputers with AI. Performance is measured based on the main workloads of the HPC center: astrophysics (Cosmoflow), weather (Deepcam), and molecular dynamics (Opencatalyst).
NVIDIA covers the full stack with GPU-accelerated processing, smart networking, GPU-optimized applications, and AI and HPC convergence support libraries. This approach accelerated workloads and enabled scientific innovation, the company said.
In many use cases, the parallel processing capabilities of GPUs combined with over 2,500 GPU-optimized applications can reduce the time required for HPC tasks from weeks to hours. As Nvidia continues to optimize its CUDA-X library and GPU-accelerated applications, it’s not uncommon to experience unpredictable but powerful performance boosts on the same GPU architecture.
As a result, the performance of the so-called ‘golden suite’, the most widely used scientific application, has improved more than 16 times in the past six years, and further development is expected in the future.
Nvidia also offers the latest versions of its AI and HPC software as containers in its NGC catalog to help you quickly take advantage of its powerful performance. Now, users only need to bring the application to their supercomputer, data center or cloud and run it, the company explains. [email protected]
Source: ITWorld Korea by www.itworld.co.kr.
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