InferASIC
Exploring a new hardware architecture for large-scale AI inference.
Inference accelerator cards designed for efficient transformer execution. Early-stage project in design and emulation.
Conceptual illustration of a potential InferASIC accelerator card form factor.
What InferASIC Is
InferASIC explores hardware architectures designed specifically for large-scale AI inference workloads. The project is focused on inference accelerator cards: purpose-built hardware for transformer inference, with a current design emphasis on self-contained execution on each card. System scale is being explored through deployment of many cards rather than distributed execution across cards. Work today is in architecture exploration, software emulation, and design.
Why This Direction
Hardware specialization
Inference has different requirements than training. Dedicated inference hardware can target those workloads directly.
Independent card execution
The current architecture emphasizes self-contained execution on each card. Models can be updated; the design is not locked to fixed silicon.
Inference focus
Optimizing for the inference path rather than training simplifies the design space and aligns with deployment needs.
Early exploration
Architecture and feasibility are being explored through emulation and design before any hardware commitment.
Current Focus
- Software emulation of the target pipeline and data flow
- Architecture design and tradeoff analysis
- Runtime and orchestration exploration
- Hardware feasibility and technology path research
For the thesis behind the project, see Vision. For development status and roadmap, Status. For technical or strategic inquiries, Contact.