Intel’s Innovations Propel Supercomputing into a New Era of Scientific Advancement

At the recent SC23 event, Intel made a significant showcase of its AI-accelerated high-performance computing (HPC) capabilities. The company demonstrated its leadership performance in handling HPC and AI workloads through a combination of its Data Center GPU Max Series, Gaudi 2 AI accelerators, and Xeon processors.

One of the highlights of Intel’s presentation was its partnership with Argonne National Laboratory on the Aurora generative AI (genAI) project. The project aims to develop state-of-the-art foundational AI models for scientific research. Specifically, Intel provided an update on the 1 trillion parameter GPT-3 LLM running on the Aurora supercomputer, thanks to the unique architecture of the Max Series GPU and the system capabilities of Aurora.

Intel and Argonne showcased the acceleration of scientific applications through the Aurora Early Science Program (ESP) and the Exascale Computing Project. They demonstrated the ability to efficiently handle 1 trillion-parameter models with just 64 nodes, paving the way for scaling the training of such models on thousands of nodes.

Deepak Patil, Intel’s corporate vice president and general manager of Data Center AI Solutions, emphasized the company’s commitment to delivering innovative technology solutions for the HPC and AI community. He highlighted the performance of Intel’s Xeon CPUs, Max GPUs, and Gaudi accelerators in propelling research and science.

The importance of generative AI for science was underscored by Argonne National Laboratory. The genAI project aims to train AI models on scientific texts, code, and datasets from diverse scientific domains, including biology, cancer research, climate science, cosmology, and materials science. The collaboration between Argonne, Intel, and other partners will enable breakthroughs in these scientific disciplines.

Intel also showcased its hardware and software optimizations for HPC and AI. For example, they demonstrated superior performance for financial industry workloads compared to nVidia GPUs. They also highlighted the improved support for AI models, including large language models like GPT-J and LLAMA2, on their Max Series GPUs.

In terms of future developments, Intel announced the upcoming release of Gaudi3 AI accelerators in 2024. These accelerators will build upon the high-performance architecture of Gaudi2 and offer even greater compute power, networking bandwidth, and memory capacity to meet the growing demand for high-performance computing.

Additionally, Intel’s next-generation GPU for AI and HPC, Falcon Shores, was introduced. Falcon Shores will leverage the intellectual property from Gaudi and Xe architectures and provide a unified programming interface through oneAPI. This will ensure seamless migration of applications from current Intel Gaudi AI accelerators and Max Series GPUs to Falcon Shores in the future.

Overall, Intel’s showcase at SC23 demonstrated its commitment to delivering tailored solutions for HPC and AI customers. The combination of their powerful hardware, software-defined approach with oneAPI, and strategic partnerships with research institutions like Argonne National Laboratory positions them as a key player in the field of AI-accelerated high-performance computing.

Background Information

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About Intel:

Intel Corporation, a global technology leader, is for its semiconductor innovations that power computing and communication devices worldwide. As a pioneer in microprocessor technology, Intel has left an indelible mark on the evolution of computing with its processors that drive everything from PCs to data centers and beyond. With a history of advancements, Intel's relentless pursuit of innovation continues to shape the digital landscape, offering solutions that empower businesses and individuals to achieve new levels of productivity and connectivity.

  

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About nVidia:

NVIDIA has firmly established itself as a leader in the realm of client computing, continuously pushing the boundaries of innovation in graphics and AI technologies. With a deep commitment to enhancing user experiences, NVIDIA's client computing business focuses on delivering solutions that power everything from gaming and creative workloads to enterprise applications. for its GeForce graphics cards, the company has redefined high-performance gaming, setting industry standards for realistic visuals, fluid frame rates, and immersive experiences. Complementing its gaming expertise, NVIDIA's Quadro and NVIDIA RTX graphics cards cater to professionals in design, content creation, and scientific fields, enabling real-time ray tracing and AI-driven workflows that elevate productivity and creativity to unprecedented heights. By seamlessly integrating graphics, AI, and software, NVIDIA continues to shape the landscape of client computing, fostering innovation and immersive interactions in a rapidly evolving digital world.

  

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Technology Explained

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GPU: GPU stands for Graphics Processing Unit and is a specialized type of processor designed to handle graphics-intensive tasks. It is used in the computer industry to render images, videos, and 3D graphics. GPUs are used in gaming consoles, PCs, and mobile devices to provide a smooth and immersive gaming experience. They are also used in the medical field to create 3D models of organs and tissues, and in the automotive industry to create virtual prototypes of cars. GPUs are also used in the field of artificial intelligence to process large amounts of data and create complex models. GPUs are becoming increasingly important in the computer industry as they are able to process large amounts of data quickly and efficiently.

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LLM: A Large Language Model (LLM) is a highly advanced artificial intelligence system, often based on complex architectures like GPT-3.5, designed to comprehend and produce human-like text on a massive scale. LLMs possess exceptional capabilities in various natural language understanding and generation tasks, including answering questions, generating creative content, and delivering context-aware responses to textual inputs. These models undergo extensive training on vast datasets to grasp the nuances of language, making them invaluable tools for applications like chatbots, content generation, and language translation.

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Xeon: The Intel Xeon processor is a powerful and reliable processor used in many computer systems. It is a multi-core processor that is designed to handle multiple tasks simultaneously. It is used in servers, workstations, and high-end desktop computers. It is also used in many embedded systems, such as routers and switches. The Xeon processor is known for its high performance and scalability, making it a popular choice for many computer applications. It is also used in many cloud computing applications, as it is capable of handling large amounts of data and providing high levels of performance. The Xeon processor is also used in many scientific and engineering applications, as it is capable of handling complex calculations and simulations.

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