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​Furiosa RNGD delivers the predictable, high-performance inference necessary for today’s massive AI workloads. This architecture overcomes legacy GPU bottlenecks by utilizing a programmable dataflow for granular control over matrix and tensor operations, alongside 256MB of on-chip SRAM and 48GB of HBM for efficient data movement.

​Furiosa Kernel Programming Model transforms RNGD into a foundational platform by granting developers direct, uncompromised access to the hardware. By bypassing generic compiler overhead through manual control over instruction scheduling and memory management, engineers can craft bespoke, high-efficiency kernels. Through this approach, we are building a vibrant ecosystem dedicated to pushing the boundaries of AI infrastructure.

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​Dr. Jeehoon Kang is the Chief Research Officer (CRO) at FuriosaAI. Before joining the industry, he was an Associate Professor of Computer Science at KAIST after receiving his Ph.D. under the supervision of Prof. Chung-Kil Hur at Seoul National University. As a specialist in concurrency, compilers, and software verification, he has published over 30 papers in premier venues such as MICRO, ASPLOS, SOSP, and PLDI.

​At FuriosaAI, Dr. Kang applies his academic expertise in computer systems to solve engineering challenges in industrial-scale deployment. He leads the development of kernel programming models to maximize the performance of the RNGD accelerator, alongside building the application software stack for reinforcement learning and agentic AI.