Welcome to the

AI Hardware Center

The IBM Research AI Hardware Center is a global research hub headquartered in Albany, New York. The center is focused on enabling next-generation chips and systems that support the tremendous processing power and unprecedented speed that AI requires to realize its full potential.

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Introduction

Advancing the development of computing chips and systems for AI

Today’s systems have achieved improved AI performance by infusing machine-learning capabilities with high-bandwidth CPUs and GPUs, specialized AI accelerators and high-performance networking equipment. To maintain this trajectory, new thinking is needed to accelerate AI performance scaling to match to ever-expanding AI workload complexities.

The AI Hardware Center is taking a holistic approach to building AI systems from the ground up – from materials, chips, devices, architecture and the entire software stack. IBM, working with NY State and a broader ecosystem of partners, is paving the way for the next generation of artificial intelligence systems that will improve business and the lives of people all over the world.

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The IBM Research AI Hardware Center enables IBM and its partner ecosystem to overcome current machine-learning limitations through novel approaches using digital AI cores and analog AI cores. A new testbed, will enable researcher to experiment with systems that meet the demands of deep learning inference and training processes, and the center is working towards the delivery of specialized accelerator cores and chip architectures.

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Our researchers also played a pivotal part in creating IBM Cloud Functions, IBM Kubernetes Service, Multicloud Manager and Key Protect, as well as the development and adoption of Istio as an enterprise service mesh. Our teams were also core contributors to the IBM Cloud Gen 2 control plane and SDN.

Each of these achievements builds upon the last to ensure IBM Cloud users have access to the latest breakthroughs in cloud technology.

Focus areas

Analog AI Cores

Analog AI Cores enable in-memory storage and processing of data to speed computation and yield exponential gains in computational efficiency.

Digital AI Cores

Digital AI Cores are new accelerators for existing semiconductor technologies that use reduced precision to speed computation and decrease power consumption.

Heterogeneous Integration

AI applications drive the need for a system level optimization of AI Hardware through Heterogeneous Integration of Accelerators, Memory and CPU. The AI Hardware center will focus on interconnect solutions to enable high speed, high bandwidth connectivity between the different components.

AI Technology testbed

The IBM Research AI Hardware Center will host research and development, prototyping, testing, and simulation activities for new AI cores specially designed for training and deploying advanced AI models, including a testbed in which members can demonstrate Center innovations in real-world applications. The testbed is a customizable platform for testing the accuracy and efficiency of new AI technologies for training and inferencing on image, speech, and text workloads.








Partners and collaborators

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Partnerships within an open ecosystem are key to advancing hardware and software innovation that are the foundation of AI. Design, development, and optimization of next-generation AI processors requires a cross-disciplinary approach that leverages the unique strengths of different organizations.

Industry partners - including fabless companies, semiconductor manufacturers, AI practitioners, and consumers - have joined IBM and New York State to form a collaboration hub in The IBM Research AI Hardware Center.

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Spotlight

Blog

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IBM teams with industry partners to bring energy-efficient AI hardware to hybrid cloud environments


21-Oct-2020

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Website

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Analog AI: A New Design Paradigm


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Toolkit

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IBM Analog Hardware Acceleration Kit


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Demo

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Run an AI algorithm where computation and storage coexist on a single chip


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Blog

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IBM Research AI Hardware Center marks IBM AI Hardware Center with explosive gains in AI computation


10-Feb-2020

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Leadership

Mukesh Khare

Jeff Burns
Director

Mukesh Khare

Kailash Gopalakrishnan
Cores and Architecture Leader, IBM Fellow

Mukesh Khare

Kaoutar El Maghraoui 
End-Use Testbed Leader

Mukesh Khare

Lorraine Herger
End Use Testbed Leader

Mukesh Khare

Vijay Narayanan
Analog Elements Leader, IBM Fellow

Mukesh Khare

Mukta Farooq
Heterogeneous Integration Leader

Mukesh Khare

Dale McHerron, 
Almaden Technical Leader

Mukesh Khare

Cindy Goldberg 
Program Director

Mukesh Khare

Abu Sebastian, 
Distinguished RSM 

Mukesh Khare

Geoffrey Burr, 
Almaden Technical Leader

Mukesh Khare

Kohji Hosokawa, 
Tokyo Technical Leader

Contact us

Contact us for additional information on how
 to join the AI Hardware Center.

Email us at ibmaihw@us.ibm.com