About me
I am a fourth-year Ph.D. student affiliated with the research group led by Prof. Peipei Zhou at the Brown University.
My research focuses on computer systems and architecture, with an emphasis on building efficient and scalable heterogeneous computing systems. I am particularly interested in rethinking the system including GPUs, CPUs, FPGAs, storage, and emerging I/O devices to support increasingly data-intensive and AI workloads.
What i'm doing
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GPU-initiated I/Os [See Demo!]
GPU-initiated I/O enables the GPU to directly issue and manage storage operations, eliminating CPU intervention to reduce latency and improve overlap between computation and data movement.
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Heterogeneous Systems
Coordinating different hardware platforms including GPUs, SSDs, FPGAs, etc., together for tasks with heterogeneous workloads.
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Applications
Several data-intensive applications have been explored, including DLRM and graph analytics, along with computational workloads such as large integer multiplication, Rivest-Shamir-Adleman (RSA), Mandelbrot set generation, and homomorphic encryption.
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Hardware Accelerator
It involves developing hardware and software together to better integrate and optimize the overall system for improved performance and efficiency.
