At the ISC High Performance Conference, Intel showcased leadership performance for high performance computing (HPC) and artificial intelligence (AI) workloads; shared its portfolio of future HPC and AI products, unified by the oneAPI open programming model; and announced an ambitious international effort to use the Aurora supercomputer to develop generative AI models for science and society.
“Intel is committed to serving the HPC and AI community with products that help customers and end-users make breakthrough discoveries faster,” said Jeff McVeigh, Intel corporate vice president and general manager of the Super Compute Group. “Our product portfolio spanning Intel® Xeon® CPU Max Series, Intel® Data Center GPU Max Series, 4th Generation Intel® Xeon® Scalable Processors and Habana® Gaudi®2 are outperforming the competition on a variety of workloads, offering energy and total cost of ownership advantages, democratizing AI and providing choice, openness and flexibility.”
At the ISC High Performance Conference in Hamburg, Germany, Jeff McVeigh, corporate vice president and general manager of the Super Compute Group at Intel, offered a presentation about how artificial intelligence (AI) is accelerating high performance computing (HPC). As part of his talk on May 22, 2023, McVeigh disclosed performance data for Intel’s HPC and AI products, announced the latest updates with Argonne National Laboratory and outlined Intel’s HPC roadmap. (Credit: Intel Corporation)
Hardware Performance at Scale
At the Intel special presentation, McVeigh highlighted the latest competitive performance results across the full breadth of hardware and shared strong momentum with customers.
Customers have recently announced new installations with Intel 4th Gen Xeon and Max Series processors:
Additionally, the Cambridge Open Zettascale Lab at the University of Cambridge has deployed the first Max GPU testbed in the United Kingdom and is seeing positive early results on molecular dynamics and biological imaging applications. Also, RIKEN announced a memorandum of understanding (MoU) with Intel aimed at accelerating joint research and development in the field of advanced computing technologies, such as AI, HPC and quantum computing. As part of the MoU, RIKEN will also engage with Intel Foundry Services to create prototypes of these new solutions.
Competitive Processors for Every Workload
Dynamic, emerging HPC and AI workloads require a full portfolio of hardware and software solutions. McVeigh provided an overview of Intel’s data center offerings that deliver many choices and solutions for the HPC community, helping to democratize AI.
In his presentation, McVeigh introduced Intel’s next-generation CPUs to meet high memory bandwidth demands. Intel led the ecosystem to develop a new type of DIMM – Multiplexer Combined Ranks (MCR) – for Granite Rapids. MCR achieves speeds of 8,800 megatransfers per second based on DDR5 and greater than 1.5 terabytes/second (TB/s) of memory bandwidth capability in a two-socket system. This boost in memory bandwidth is critical for feeding the fast-growing core counts of modern CPUs and enabling efficiency and flexibility.
Intel also disclosed a new, AI-optimized x8 Max Series GPU-based subsystem from Supermicro, designed to accelerate deep learning training. In addition to access via Intel® Developer Cloud beta5 later this year, multiple OEMs will offer solutions with Max Series GPUs x4 and x8 OAM subsystems and PCIe cards, which will be available in the summer.
Intel’s next-generation Max Series GPU, Falcon Shores, will give customers the flexibility to implement system-level CPU and discrete GPU combinations for the new and fast-changing workloads of the future. Falcon Shores is based on a modular, tile-based architecture and will:
Argonne National Laboratory, in collaboration with Intel and HPE, announced plans to create a series of generative AI models for the scientific research community.
“The project aims to leverage the full potential of the Aurora supercomputer to produce a resource that can be used for downstream science at the Department of Energy labs and in collaboration with others,” said Rick Stevens, Argonne associate laboratory director.
These generative AI models for science will be trained on general text, code, scientific texts and structured scientific data from biology, chemistry, materials science, physics, medicine and other sources.
The resulting models (with as many as 1 trillion parameters) will be used in a variety of scientific applications, from the design of molecules and materials to the synthesis of knowledge across millions of sources to suggest new and interesting experiments in systems biology, polymer chemistry and energy materials, climate science and cosmology. The model will also be used to accelerate the identification of biological processes related to cancer and other diseases and suggest targets for drug design.
Argonne is spearheading an international collaboration to advance the project, including Intel; HPE; Department of Energy laboratories; U.S. and international universities; nonprofits; and international partners, such as RIKEN.
Additionally, Intel and Argonne National Laboratory highlighted installation progress, system specs and early performance results for Aurora:
Intel has completed the physical delivery of more than 10,000 blades for the Aurora supercomputer.
Aurora’s full system, built using HPE Cray EX supercomputers, will have 63,744 GPUs and 21,248 CPUs and 1,024 DAOS storage nodes. And it will utilize the HPE Slingshot high-performance Ethernet network.
Early results show leading performance on real-world science and engineering workloads, with up to 2x performance over AMD MI250 GPUs, 20% improvement over H100 on the QMCPACK quantum mechanical application, and near linear scaling up to hundreds of nodes.2
Aurora is expected to offer more than 2 exaflops of peak double-precision compute performance when launched this year.
Productive, Open Accelerated Computing Through oneAPI
Worldwide, about 90% of all developers benefit from or use software developed for or optimized by Intel.6 Since the oneAPI programming model launched in 2020, developers have demonstrated oneAPI on diverse CPU, GPU, FPGA and AI silicon from multiple hardware providers, addressing the challenges of single-vendor accelerated programming models. The latest Intel oneAPI tools deliver speedups for HPC applications with OpenMP GPU offload, extend support for OpenMP and Fortran, and accelerate AI and deep learning through optimized frameworks, including TensorFlow and PyTorch, and AI tools, enabling orders of magnitude performance improvements.
oneAPI makes multiarchitecture programming easier for programmers through oneAPI’s SYCL implementation, oneAPI plug-ins for Nvidia and AMD processors developed by Codeplay, and the Intel® DPC++ Compatibility Tool (based on open source SYCLomatic) that migrates code from CUDA to SYCL and C++ where 90-95% of code typically migrates automatically.7 The resulting SYCL code shows comparable performance with the same code running on Nvidia- and AMD-native systems languages. Data shows SYCL code for the DPEcho astrophysics application running on the Max Series GPU outperforms the same CUDA code on Nvidia H100 by 48%.1
The broader ecosystem is embracing SYCL, as well. Eviden, an Atos business, announced CEPP one+ with Intel, an HPC/AI Code modernization service based on Eviden’s Center of Excellence in Performance Programming (CEPP). CEPP one+ will focus on the adoption of SYCL and OpenMP, preparing the community for a heterogeneous computing landscape while providing freedom of choice in hardware through open standards.
Disclaimers and configuration:
1 Visit the International Supercomputing Conference (ISC’23) page on intel.com/performanceindex for workloads and configurations. Results may vary.
2 Intel does not control or audit third-party data. You should consult other sources to evaluate accuracy.
3 Hyperion Research HPC Market Update, Nov. 2022.
4 Intel® Xeon® 8480+ has 1.5x higher geomean HPC performance across 27 benchmarks and applications than AMD EPYC 7763. Results may vary.
5 The Intel Developer Cloud beta is currently available to select prequalified customers.
6 According to Intel estimates.
7 Intel estimates as of March 2023. Based on measurements on a set of 85 HPC benchmarks and samples, with examples like Rodinia, SHOC, PENNANT. Results may vary.
Performance varies by use, configuration and other factors. Performance results are based on testing as of dates shown in configurations and may not reflect all publicly available updates. No product or component can be absolutely secure.
Your costs and results may vary.
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Statements in this document that refer to future plans or expectations are forward-looking statements. These statements are based on current expectations and involve many risks and uncertainties that could cause actual results to differ materially from those expressed or implied in such statements. For more information on the factors that could cause actual results to differ materially, see our most recent earnings release and SEC filings at www.intc.com.