Jian Weng, PhD student, Computer Science Department, UCLA
Sunday, February 12, 2023, 08:30
In reaction to the waning benefit of transistor scaling and the increasing demands on computing power, specialized accelerators have drawn significant attention from both academics and industry because of their orders-of-magnitude performance improvement and energy efficiency. All these accelerators require non-trivial human efforts, from designing the architecture to having a full-stack implementation. Therefore, the software/hardware co-designed innovations are often monopolized by several large teams in large companies. In this talk, I will first discuss how my research democratizes the accelerator designs and unifies the hardware/software innovations by automating the accelerator design process under a unified programming paradigm. By taking advantage of the compiler’s awareness of the program behaviors that profit from hardware specialization, accelerators can be automatically synthesized by searching through a well-defined design space. These automatically designed accelerators achieve comparable cost/performance efficiency compared with prior handcrafted designs. In the rest of the talk, I will also cover how this work inspires me to develop techniques to accelerate emerging application domains by orders-of-magnitude speedup, including digital signal processing and DNN inference, and how I take advantage of this work to revolutionize the FPGA programming paradigm.