At ISC’23, Intel details competitive
performance for diverse HPC and AI workloads, from memory-bound to
generative AI, and introduces new science LLM initiative to
democratize AI.
NEWS HIGHLIGHTS
- Intel’s broad portfolio of HPC and AI products provides
competitive performance, with Intel® Data Center GPU Max Series
1550 showing an average speedup of 30% over Nvidia H100 on a wide
range of scientific workloads.1
- Product roadmap updates highlight Granite Rapids, a
next-generation CPU to address memory bandwidth demands, and Falcon
Shores GPU to meet an expanding, diverse set of workloads for HPC
and AI.
- Argonne National Laboratory and Intel announce full Aurora
specifications, system momentum and international initiative with
Hewlett Packard Enterprise (HPE) and partners to bring the power of
generative AI and large language models (LLM) to science and
society.
- Enhanced oneAPI and AI tools help developers speed up HPC and
AI workloads and enhance code portability across multiple
architectures.
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.
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Intel is committed to serving the high
performance computing (HPC) and artificial intelligence (AI)
communities with products that help customers and end-users make
breakthrough discoveries faster. Intel’s product portfolio –
spanning Intel® Xeon® CPU Max Series, Intel® Data Center GPU Max
Series, 4th Gen Intel® Xeon® Scalable processors and Habana®
Gaudi®2 processors – meets the needs of the HPC community. At the
same time, oneAPI and AI tools help developers speed up HPC and AI
workloads and enhance code portability across multiple
architectures. (Credit: Intel Corporation)
More: International Supercomputing Conference 2023 (Quote
Sheet)
“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.”
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.
- The Intel® Data Center GPU Max Series outperforms Nvidia H100
PCIe card by an average of 30% on diverse workloads1, while
independent software vendor Ansys shows a 50% speedup for the Max
Series GPU over H100 on AI-accelerated HPC applications.2
- The Xeon Max Series CPU, the only x86 processor with high
bandwidth memory, exhibits a 65% improvement over AMD’s Genoa
processor on the High Performance Conjugate Gradients (HPCG)
benchmark1, using less power. High memory bandwidth has been noted
as among the most desired features for HPC customers.3
- 4th Gen Intel Xeon Scalable processors – the most widely used
in HPC – deliver a 50% average speedup over AMD’s Milan4, and
energy company BP’s newest 4th Gen Xeon HPC cluster provides an 8x
increase in performance over its previous-generation processors
with improved energy efficiency.2
- The Gaudi2 deep learning accelerator performs competitively on
deep learning training and inference, with up to 2.4x faster
performance than Nvidia A100.1
Customers have recently announced new installations with Intel
4th Gen Xeon and Max Series processors:
- Kyoto University is deploying 4th Gen Xeon for Laurel 3 and
Cinnamon 3, and Xeon Max Series processors for Camphor 3.
- Cineca deployed Leonardo with 4th Gen Intel Xeon
processors.
- University of Rochester - Laboratory for Laser Energetics is
deploying a cluster with 4th Gen Xeon processors.
- Servicio Meteorológico Nacional de Argentina will deploy a
system with both Max Series CPUs and GPUs.
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 artificial intelligence,
high performance computing 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:
- Support HPC and AI data types, from FP64 to BF16 to FP8.
- Enable up to 288GB of HBM3 memory with up to 9.8TB/s total
bandwidth and vastly improved high-speed I/O.
- Empower the CXL programming model.
- Present a unified GPU programming interface through
oneAPI.
Generative AI for Science
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.
About Intel
Intel (Nasdaq: INTC) is an industry leader, creating
world-changing technology that enables global progress and enriches
lives. Inspired by Moore’s Law, we continuously work to advance the
design and manufacturing of semiconductors to help address our
customers’ greatest challenges. By embedding intelligence in the
cloud, network, edge and every kind of computing device, we unleash
the potential of data to transform business and society for the
better. To learn more about Intel’s innovations, go to
newsroom.intel.com and intel.com.
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.
Intel technologies may require enabled hardware, software or
service activation.
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.
© Intel Corporation. Intel, the Intel logo and other Intel marks
are trademarks of Intel Corporation or its subsidiaries. Other
names and brands may be claimed as the property of others.
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Bats Jafferji 1-603-809-5145 bats.jafferji@intel.com
Intel (NASDAQ:INTC)
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