Toward Open-Source Chiplets for HPC and AI: Occamy and Beyond
By Paul Scheffler 1, Thomas Benz 1, Tim Fischer 1, Lorenzo Leone 1, Sina Arjmandpour 1, Luca Benini 1,2
1 Integrated Systems Laboratory, ETH Zurich, Switzerland
2 Department of Electrical, Electronic, and Information Engineering, University of Bologna, Italy
Abstract
We present a roadmap for open-source chiplet-based RISC-V systems targeting high-performance computing and artificial intelligence, aiming to close the performance gap to proprietary designs. Starting with Occamy, the first open, silicon-proven dual-chiplet RISC-V manycore in 12nm FinFET, we scale to Ramora, a mesh-NoC-based dual-chiplet system, and to Ogopogo, a 7nm quad-chiplet concept architecture achieving state-of-the-art compute density. Finally, we explore possible avenues to extend openness beyond logic-core RTL into simulation, EDA, PDKs, and off-die PHYs.
Index Terms—Chiplets, RISC-V, HPC, NoC, AI, Machine Learning
To read the full article, click here
Related Chiplet
- Integrated voltage regulator (IVR) chiplet
- High-performance connectivity chiplets
- eFPGA Chiplet
- DPIQ Tx PICs
- IMDD Tx PICs
Related Technical Papers
- PICNIC: Silicon Photonic Interconnected Chiplets with Computational Network and In-memory Computing for LLM Inference Acceleration
- CarbonPATH: Carbon-aware pathfinding and architecture optimization for chiplet-based AI systems
- DeepStack: Scalable and Accurate Design Space Exploration for Distributed 3D-Stacked AI Accelerators
- CHIPSMORE: Compute-in-Interconnect and -Memory Chiplets for Multi-Mode Multi-Request LLM Inference Acceleration
Latest Technical Papers
- Fengshui: Demystifying Chiplet Ecosystem and Bespoke Neural Network Accelerator Codesign
- Hardware Trojan Threats to Multi-Chiplet Photonic Neural Network Accelerators
- Mapping Dynamic, Hierarchical Quantum Circuits
- Chiplet-Based Techniques for Scalable and Memory-Aware Multiscalar Multiplication on Hardware Platforms
- A Time-Encoded Analog Photonic Interposer for Energy-Efficient Integration of Analog Vision Sensors and Analog Accelerators