We research hardware-software co-design, memory and caching runtimes, and low-latency execution engines. Our focus is on the core computational bottlenecks of modern systems—optimizing memory bandwidth, reducing inference latency, and making AI workloads run with lower resource overhead.
Computer chips rarely run at full speed because standard software isn't tailored to their exact physical limits. We write specialized code directly for GPU processors so AI calculations finish up to 3.5× faster.
The biggest slowdown in modern AI isn't the math—it's waiting for data to travel from memory to the processor. We redesign how information flows so computers never wait on stalled data.
When you speak to an AI voice coach or pilot a drone, even a 50-millisecond delay feels broken. We build ultra-lean software execution engines that respond in under 15 milliseconds under massive load.
Most AI requires giant cloud server rooms. We condense models so they can run locally on spatial VR headsets, edge robots, and iPhones without draining battery or needing constant internet.