HPC Forge

HPC Forge is a scalable scientific machine learning research lab at the University of California, Irvine. Check out our recent Publications to see what we do.

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 at the intersection of scientific machine learning and high-performance computing. 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.

Interests

  • Scientific machine learning
  • Neural solvers
  • Foundational models for science
  • High-performance computing
  • Performance analysis and modeling

Education

  • PhD in Computational Science and Engineering, 2013

    Georgia Institute of Technology

  • BE in Computer Science and Engineering, 2007

    Anna University

The Lab

PhD Students

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Arthur Feeney

PhD student, EECS, 2022-present

  • MS in Computer Science, University of Massachusetts Amherst, 2021

  • BS in Computer Science, Trinity University, 2019

Current research: Machine Learning for PDEs, MD, and Lattices

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Zitong Li

PhD student, EECS, 2022-present

  • MS in Computer Science, Wake Forest University, 2022

  • BS in Computer Science, University of Nebraska-Lincoln, 2018

Current research: Sparse Kernels for Tensor Cores

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Shakeel Hassan

MS/PhD student, EECS, 2022-present

  • BTech in Electronics and Communication Engineering, National Institute of Technology Trichy, 2020

Current research: Autoregressive Neural Operators for Long-range Dynamics

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Xianwei Zou

PhD student, EECS, 2024-present

  • MS in Electrical and Computer Engineering, Carnegie Mellon University, 2024

  • BE in Telecommunication Engineering, Xidian University, 2021

Current research: Scalable Foundational Models for Science

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Kuei-Hsiang Huang

MS/PhD student, EECS, 2024-present

  • BS in Mathematics, National Tsing Hua University, 2024

Current research: Domain Decomposed Neural Operators for PDEs

Alumni

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Srikar Arani

EECS MS (2024)

  • BS in Computer Engineering, University of California Santa Barbara, 2022

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Sebastian Barschkis

EECS MS (2023)

  • BS in Computer Science, Ludwig Maximilian University of Munich, 2018

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Octavi Obiols Sales

MAE PhD (2022)

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Behnam Pourghassemi

EECS PhD (2021)

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Hengjie Wang

MAE PhD (2021)

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Shu-Mei Tseng

EECS MS (2021)

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Rohit Zambre

EECS PhD (2020)

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Laleh Beni

CS PhD (2019)

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Ferran Marti

Postdoctoral Scholar (2017 - 2018)

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Bahareh Davani

EECS MS (2016)

Recent Publications

Wael Fatnassi, Arthur Feeney, Aparna Chandramowlishwaran, Yasser Shoukry
October 2024 IEEE Transactions on Computer-Aided Design (IEEE TCAD)

BERN-NN-IBF: Enhancing Neural Network Bound Propagation Through Implicit Bernstein Form and Optimized Tensor Operations

PDF Project
Youngjoon Suh, Aparna Chandramowlishwaran, Yoonjin Won
March 2024 npj Computational Materials

Recent progress of artificial intelligence for liquid-vapor phase change heat transfer

PDF Project
Sheikh Md Shakeel Hassan, Arthur Feeney, Akash Dhruv, Jihoon Kim, Youngjoon Suh, Jaiyoung Ryu, Yoonjin Won, Aparna Chandramowlishwaran
December 2023 Neural Information Processing Systems Datasets and Benchmarks Track (NeurIPS Spotlight)

BubbleML: A Multiphysics Dataset and Benchmarks for Machine Learning

PDF Project
Arthur Feeney, Zitong Li, Ramin Bostanabad, Aparna Chandramowlishwaran
November 2023 Proc. ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (SC)

Breaking Boundaries: Distributed Domain Decomposition with Scalable Physics-Informed Neural PDE Solvers

PDF Project
Octavi Obiols-Sales, Abhinav Vishnu, Nicholas Malaya, Aparna Chandramowlishwaran
August 2023 International Conference on Parallel Processing (ICPP)

ADARNet: Deep Learning Predicts Adaptive Mesh Refinement

PDF Project Project
See all publications

Projects

HiPer

A CFD solver for high-performance turbulent flow simulations

Machine & Deep Learning

HPC for accelerating ML/DL and DL for science

Recent & Upcoming Talks

Transferable Deep Learning Surrogates for Solving PDEs

May 6, 2021 — Worldwide online event

SPCL_Bcast online seminar at ETH Zurich

Aparna Chandramowlishwaran
Project Project Watch

Only Relative Speed Matters -- Virtual Causal Profiling

November 2, 2020 — November 6, 2020 Online

IFIP Performance

Behnam Pourghassemi
Slides Watch

Scalable Web Performance Analysis Using Causal Profiling

August 4, 2020 — August 5, 2020 Online

Google Future of the Mobile Web Workshop

Behnam Pourghassemi

On the Limits of Parallelizing Convolutional Neural Networks on GPUs

July 14, 2020 — July 16, 2020 Online

ACM Symposium on Parallelism in Algorithms and Architectures (SPAA)

Behnam Pourghassemi
Project Watch

CFDNet - A deep learning-based accelerator for fluid simulations

June 29, 2020 — July 2, 2020 Worldwide online event

ACM International Conference on Supercomputing (ICS)

Octavi Obiols Sales
Project Project Watch
See all talks