Building PyTorch-native support for the IBM Spyre Accelerator
Technical note
Viji Srinivasan, Raghu Ganti, Mudhakar Srivatsa, Elpida Tzortzatos, Tabari Alexander, and Vaidyanathan Srinivasan
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
Lifting the cover on the IBM Spyre Accelerator
Technical noteJeffrey BurnsIt takes a village to make open infrastructure for AI a reality
NewsPeter HessExpanding AI model training and inference for the open-source community
NewsPeter HessBuilding the IBM Spyre Accelerator
ReleasePeter HessIBM researchers win prestigious European grants
NewsPeter Hess and Mike Murphy- See more of our work on AI Hardware
Projects
Neuro-inspired AI to optimize learning and computing efficiency of next generation AI.
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
Advanced Acoustic Emission (AE) Sensing and Analytics Scheme for In-situ Warpage Characterizations of Flip-Chip Packaging
- Yigit Turan
- Xinchen Wang
- et al.
- 2026
- ECTC 2026
PosterA Scalable Oscillatory Neural Network Architecture Using Analog Resistive Memory for Coupling Elements
- Wooseok Choi
- Thomas Van Bodegraven
- et al.
- 2026
- MATSUS 2026
Invited talkEliminating Redundancy: Ultra-compact Code Generation for Programmable Dataflow Accelerators
- Prasanth Chatarasi
- Alex Gatea
- et al.
- 2026
- CGO 2026
Conference paperAlgorithm Architecture Co-Design for Analog In-Memory Computing
- 2026
- ISSCC 2026
Workshop paperSpyre: An inference-optimized scalable AI accelerator for enterprise workloads
- Matt Cohen
- Monodeep Kar
- et al.
- 2026
- ISSCC 2026
Conference paperEnabling Spill-Free Compilation via Affine-Based Live Range Reduction Optimization
- Prasanth Chatarasi
- Alex Gatea
- et al.
- 2026
- CGO 2026
Conference paper
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