March 20, 2019 — Researchers in industry can now solve their most complex modeling and simulation challenges faster. The powerful iForge cluster at the National Center for Supercomputing Applications (NCSA) at Illinois provides our partners in industry with the compute resources and user support they need to coax efficient performance and increased productivity out of even the most complex industrial applications. Our new GPU queue builds on this mission by offering fast new technology that’s already solving bigger problems in less time. With the latest NVIDIA V100 GPUs and NVlink interconnect, our partner engineers and scientists can get more from their machine learning and engineering applications. Initial benchmarks are already showing the benefits of running applications on the iForge GPU queue, which currently offers two 40-core, 192 GB Skylake nodes, each equipped with four NVIDIA Tesla V100 32 GB GPU cards (for a total of eight GPUs).
EDEM, a leading commercial Discrete Element Modeling software used for particle and bulk materials research, saw significant speedups on the iForge GPU queue when compared to Skylake CPU alone, especially when scaling across GPUs. In one series of comparisons, simulating 0.01 seconds of particle flow for 17 million particles in a slowly rotating box took 6.9 hours on 12 CPU cores, while using four GPU cards and just four CPU cores lowered the walltime to only 13.5 minutes. After accounting for ancillary processes, the EDEM solver speedup was shown to reach 60 times! NCSA’s high-memory 32 GB GPUs also demonstrated computational advantages over standard GPUs: EDEM tests that had previously run out of memory with 16 GB GPUs were able to complete on the NCSA queue.
In the field of Finite Element Analysis (FEA), NCSA tested major software Abaqus/Standard using a challenging non-linear problem with high fidelity meshes and almost 17 million degrees of freedom. Abaqus/Standard showed a two-time speedup using two CPU nodes each accelerated with four GPU cards versus two CPU nodes alone. Seid Koric, Technical Assistant Director of NCSA and a Research Professor in the Mechanical Science and Engineering Department at Illinois, stated that to the best of his knowledge, “this is the first time that a commercial CAE code has exhibited this level of acceleration on multiple nodes with multiple GPU cards.”
Machine learning also presents a strong use case for GPUs, as training machine learning models using tools like Tensorflow requires a tremendous amount of data processing that GPUs can help accelerate. NCSA ran CIFAR10 CNN benchmarks with Tensorflow using one or more GPU cards. In testing where Tensorflow employed a single GPU, it enabled processing of 10 times more training images/second than an equivalent CPU node. When scaling across all four GPU cards on one node with multi-tower programming, results showed a 40-time increase in training samples processed per second compared to one CPU node. The superior processing of GPUs enables better-trained, more reliable machine learning models in less time.
While further benchmarks will help develop a more complete picture of how and when iForge’s new GPUs can best benefit research, the first round of results demonstrate significant gains for engineering and machine learning applications. If you have interesting use cases, have suggestions, or need additional benchmarks please email us at [email protected].
The National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign provides supercomputing and advanced digital resources for the nation’s science enterprise. At NCSA, University of Illinois faculty, staff, students, and collaborators from around the globe use advanced digital resources to address research grand challenges for the benefit of science and society. NCSA has been advancing one third of the Fortune 50® for more than 30 years by bringing industry, researchers, and students together to solve grand challenges at rapid speed and scale.
About NCSA Industry
The NCSA Industry Program combines a highly experienced technical team with state-of-the-art high performance digital resources to perform grand scale consulting to help businesses gain a competitive edge. We have worked with many of the world’s largest companies in sectors including manufacturing, oil and gas, finance, retail/wholesale, bio/medical, life sciences, agriculture, technology, and more.