INTRODUCING IP‌‍U-MA‍C‍HINE A‌ND‌ IP‌U-P‌OD‌ SYSTEMS

Second generation IPU systems for AI infrastructure at scale

IPU-Machine: M2000

Our second generation, core building block for AI infrastructure, for all your AI workloads. Available standalone to get started and with built-in networking for supercomputing scale, the IPU-M2000 packs 1 PetaFlop of AI compute and 450GB Exchange-Memory. Available to pre-order today.

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IPU-POD₆₄

Building blocks and reference designs for AI supercomputing scale that every enterprise can benefit from. Graphcore IPU-POD₆₄ incorporates transformative innovations in compute and networking. Available to test today in our private Graphcloud™ preview.

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IPU-Server systems

Industry standard OEM server systems for training and inference, based on Graphcore dual-IPU C2 PCIe Cards with MK1 Colossus™ IPUs. Get started with development and experimentation then ramp to full scale production. Available on Microsoft Azure and to buy direct from Dell, Inspur and our partners.

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BENCHMARKS

State of the Art with today’s large, complex models

Natural Language Processing - BERT

The IPU delivers over 25% faster time-to-train with the BERT language model, training BERT-base in 36.3 hours with seven C2 IPU-Processor PCIe cards, each with two IPUs, in an IPU Server system. For BERT inference, we see more than 2x higher throughput at the lowest latency resulting in unprecedented speedups.

Computer Vision - EfficientNet

The Graphcore C2 IPU-Processor PCIe card achieves 15x higher throughput and 14x lower latency compared to a leading alternative processor. High throughput at the lowest possible latency is key in many of the important use cases today such as visual search engines and medical imaging.

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OUR CUSTOMERS

Prof. Andrew Briggs

Professor of Nanomaterials at University of Oxford

“Creating and maintaining solid state qubits for use in quantum computers is, unsurprisingly, complex. Tuning them and keeping them stable requires analysing and controlling many sensitive variables in real-time. It is a perfect machine learning problem. The advanced AI models we use are already testing the limits of today’s accelerators. Our early work with Graphcore’s IPU has resulted in dramatic performance gains, thanks to its raw computing power, and the way it manages classic AI challenges such as sparsity. We’re tremendously excited by the announcement of Graphcore’s next generation IPU technology, and the associated computational power that will propel us further and faster into the future of quantum computing.”
Chris Seymour

Director, Advanced Platform Development at Oxford Nanopore

“We have been testing Graphcore IPUs for some time now and have been really impressed with the potential of this technology. With IPUs we’ve seen impressive throughput in some of our key areas of research. We are excited to be testing MK2 architecture and continue exploring the benefits of this innovative chip architecture”.
Dr. Kristofer Bouchard

Staff Scientist at Lawrence Berkeley National Laboratory

“By leveraging the Azure IPU preview we have seen impressive potential from the IPU, and look forward to driving new innovations on the Graphcore Mk2 platform. I expect the IPU-M2000 to enable major breakthroughs in artificial intelligence”
KS Lee

CEO at EspresoMedia

“We have been working with Graphcore IPUs for some time and we are seeing significant performance gains in a number of our machine learning workloads including video and image super resolution upscaling. We are delighted to be a lead customer for their Mk2 IPU platforms. The Mk2 IPU is extremely powerful and flexible and the IPU-M2000 offers a real breakthrough platform for us to enable our customers to make new breakthroughs in machine intelligence.”
Are Magnus Bruaset

Research Director at Simula Research Laboratory

“Our HPC department has been collaborating with Graphcore for two years, and at the end of 2019 Simula became an early access customer for their IPU-POD scale out platforms. We are impressed with Graphcore’s technology for energy-efficient construction and execution of large, next-generation ML models, and we expect significant performance gains for several of our AI-oriented research projects in medical imaging and cardiac simulations. We are also pursuing other avenues of research that can push the envelope for Graphcore’s systems, such as how to efficiently conduct large-scale, sparse linear algebra operations commonly found in physics-based HPC workloads.”
Arnaud Bertrand

SVP & Fellow, Head of Strategy, Innovation and R&D BDS at Atos

“We are partnering with Graphcore to make their MK2 IPU systems products, including IPU-M2000 and IPU-POD scale out systems, available to our customers specifically large European labs and institutions. We are already planning with European early customers to build out an IPU cluster for their AI research projects. The IPU new architecture can enable a more efficient way to run AI workloads which fits to the Atos decarbonization initiative and we are delighted to be working with a European AI semiconductor company to realise this future together.”
Girish Bablani

Corporate Vice President, Azure Compute at Microsoft Corp.

“Natural language processing models are hugely important to Microsoft – to run our internal AI workloads and for our AI customers on Microsoft Azure. We are extremely excited by the potential that this new collaboration on processors with Graphcore will deliver for our customers. The Graphcore offering extends Azure’s capabilities and our efforts here form part of our strategy to ensure that Azure remains the best cloud for AI.”
Daniele Scarpazza

R&D Team Lead

"A big focus for us at Citadel is leveraging cutting edge technology to optimize the investment process across a range of strategies and asset classes. We believe that constantly reevaluating and improving the technology we offer our investment teams helps us stay ahead of our competition. We are very excited to be working with Graphcore as one of its early access partners to test the possible applications of the new processor technology within our business. The Graphcore IPU has been designed from the ground up for machine learning and its novel architecture is already enabling us to explore new techniques that have been inefficient or simply not possible before."
CEO at Qwant

“Our research team at Qwant works at the cutting edge of AI to quickly deliver the best possible results on our users search queries while ensuring the results are neutral, impartial and accurate. It’s a tall order. We see millions of searches each day for images alone. We have been working closely with Microsoft and Graphcore to use IPU processor technology in the Azure Cloud and are seeing a significant improvement – with 3.5x higher performance - in our image search capability using ResNext on IPUs, out of the box. There is huge potential for innovation with Graphcore IPUs on new machine intelligence models and we are working on these approaches to refine our search results so that we can deliver exactly what our customers are looking for.”
Prof. Andrew Davison

Professor of Robot Vision, Department of Computing

“We believe new processor technology is going to play a key part in the evolution of Spatial AI and SLAM in the near future and have been excited to get early research access to Graphcore’s innovative new hardware. Fully general Spatial AI will require sparse probabilistic and geometric reasoning on graphs as well as computations with deep neural nets. By paying as much attention to communication as computation, Graphcore have created a new scalable architecture which we believe has the potential to execute all these algorithms with low latency and power efficiency.”