Reimagining storage for the generative AI era
Research
Talia Gershon, Mike Murphy, Swaminathan Sundararaman, Haris Pozidis, and Khanh Ngo
AI Hardware
The world is generating reams of data each day, and the AI systems built to make sense of it all constantly need faster and more robust hardware. We’re developing new devices and architectures to support the tremendous processing power AI requires to realize its full potential.
Our work
How IBM Research helped prepare the IBM z17 for tomorrow’s workloads
NewsPeter HessWhy a decades old architecture decision is impeding the power of AI computing
ExplainerPeter HessHow analog in-memory computing could power the AI models of tomorrow
ResearchPeter HessHow John Knickerbocker spent a career cultivating new technologies
Deep DivePeter HessHow low-precision computing boosts efficiency — without hurting accuracy
ExplainerPeter Hess- See more of our work on AI Hardware
Analog AI: A New Design Paradigm
At IBM Research we’re developing a new class of Analog AI hardware, purpose built to help innovators realize the promise of the next stages of AI. Journey inside this unique architecture.
Publications
On-Chip Training and Inference using Analog CMO/HfOx ReRAM Artificial Synapses
- Donato Francesco Falcone
- Victoria Clerico
- et al.
- 2025
- Neuronics 2025
Tile Efficiency is not System Efficiency – CIM architecture studies of LLMs and other large DNNs
- Pritish Narayanan
- 2025
- VLSI Technology and Circuits 2025
Heterogeneous neural processing units leveraging analog in-memory computing for edge AI
- 2025
- VLSI Technology and Circuits 2025
A 6+ GHz 128KB Multi-Port L1 Cache using Ground Rule Clean 10T Bitcells in 5nm Technology
- Rajiv Joshi
- John Davis
- et al.
- 2025
- VLSI Technology and Circuits 2025
Hardware Accelerator Design for AI: Enabling Generative Models
- Leland Chang
- 2025
- VLSI Technology and Circuits 2025
Chiplet and Heterogeneous integration Technologies for HPC and AI
- 2025
- VLSI Technology and Circuits 2025
AI Hardware Center
The IBM Research AI Hardware Center is a global research collaboration hub dedicated to creating the next generation of systems and chips for AI workloads, as well as expanding joint research efforts across technology, architecture, and algorithms.
Explore the center