May 2021 – August 2021

Software Engineering Intern


Performance Profiling for Deep Learning Frameworks
May 2020 – August 2020

Software Engineering Intern


Performance Regression Analysis of Feedback-direct Optimization (FDO) Based Programs
June 2018 – August 2018
Menlo Park

Research Intern


Neural Network Optimization on Mobiles
April 2017 – July 2017

Research Intern


Neural Network Quantization
October 2013 – February 2014

SDE Intern


Hadoop Workflow Optimization



GPA is a performance advisor for NVIDIA GPUs that suggests potential code optimization opportunities at a hierarchy of levels, including individual lines, loops, and functions. GPA uses data flow analysis to approximately attribute measured instruction stalls to their root causes and uses information about a program’s structure and the GPU to match inefficiency patterns with suggestions for optimization. GPA estimates each optimization’s speedup based on a PC sampling-based performance model.

We implemented GVProf, the first value profiler that locates value redundancy problems in applications running on GPU-based clusters. Our experiments show that GVProf incurs acceptable overhead and scales to large executions. GVProf provides useful insights to guide performance optimization. Under the guidance of GVProf, we optimized several HPC and machine learning workloads, obtaining speedups up to 1.93x.

Our tool provides a profile view and a trace view for GPU-accelerated applications. The profile view identifies where GPU APIs are invoked in CPU calling context, approximates calling context for GPU execution, and analyzes instruction mix for GPU kernels. The tool traces CPU and GPU activities for a large number of processes and threads with minimal overhead.

A fast, memory efficient, and light-weight implementation for gSpan algorithm in data mining. gBolt is up to 100x faster than the original implementation with multi-threading on a single machine. gBolt also reduces more than 200 folds memory usage, running efficiently on personal computers.

Recent Publications

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ValueExpert: exploring value patterns in GPU-accelerated applications

Project Source Document

Measurement and Analysis of GPU-Accelerated OpenCL Computations on Intel GPUs

Project Source Document

Recent & Upcoming Talks

Presented triton programming language and a deep learning profiler

Presented a talk about our value profiling tool at ASPLOS’22

Presented a poster and a talk about my PhD research at SC’21

Using HPCToolkit to Measure and Analyze the Performance of GPU-accelerated Applications Tutorial, Mar-Apr 2021

Presented our CGO’21 work.