HPC Forge

HPC Forge is a parallel computing research lab at the University of California, Irvine. We aim to advance computational science and engineering using high-performance computing and artificial intelligence. Our target platforms span single-node to large-scale systems (i.e., supercomputers). Check out the Projects tab for active projects.

We are always looking for interested and motivated students/postdocs to join our team. If you are interested in joining our research lab, please email your CV and one representative publication (if any) to amowli@uci.edu.

Hi there!

I’m an associate professor in the Department of Electrical Engineering and Computer Science at UC Irvine. My research is in the area of high-performance computing and I lead the HPC Forge research lab. I received my Ph.D in Computational Science and Engineering from Georgia Tech in 2013 in the HPC Garage. Prior to joining UCI, I was a research scientist at MIT CSAIL, where I worked on the X-Stack (exascale software stack) project.


  • High-performance computing
  • Parallel algorithms and applications
  • Performance analysis and modeling
  • Scientific and data-intensive computing
  • AI for science


  • PhD in Computational Science and Engineering, 2013

    Georgia Institute of Technology

  • BE in Computer Science and Engineering, 2007

    Anna University

The Lab

Current Members


Octavi Obiols Sales

PhD Candidate, MAE


Behnam Pourghassemi

PhD Candidate, EECS



Shu-Mei Tseng



Hengjie Wang

MAE PhD (2021)


Rohit Zambre

EECS PhD (2020)


Laleh Beni

CS PhD (2019)


Bahareh Davani

EECS MS (2016)


Ferran Marti

Postdoctoral Scholar (2017 - 2018)

Recent Publications

SURFNet: Super-resolution of Turbulent Flows with Transfer Learning using Small Datasets

Demystifying asynchronous I/O Interference in HPC applications

Logically Parallel Communication for Fast MPI+ Threads Applications

Train Once and Use Forever: Solving Boundary Value Problems in Unseen Domains with Pre-trained Deep Learning Models

adPerf: Characterizing the Performance of Third-party Ads



A CFD solver for high-performance turbulent flow simulations

High-performance Communication

A fast MPI+threads library for exascale supercomputers

Machine & Deep Learning

HPC for accelerating ML/DL and DL for science

Web browsers

Scalable dynamic analysis of web browsers

Recent & Upcoming Talks

Transferable Deep Learning Surrogates for Solving PDEs

Only Relative Speed Matters -- Virtual Causal Profiling

Scalable Web Performance Analysis Using Causal Profiling

On the Limits of Parallelizing Convolutional Neural Networks on GPUs

CFDNet - A deep learning-based accelerator for fluid simulations