๐ป Computational scientist
@ Argonne National Laboratory (ALCF)๐งช Interested in:
{AI, HPC} for science
๐ scaling large models across thousands of GPUs
๐ If youโre curious
๐ How I got here
My current research focuses on using deep generative modeling to help build better sampling algorithms in lattice gauge theory. In particular, Iโm interested in building gauge equivariant neural network architectures and using inductive priors to incorporate physical symmetries into machine learning models.
I received my PhD in Physics from the University of Iowa in 2019 and my thesis was on Learning Better Physics: A Machine Learning Approach to Lattice Gauge Theory.
Prior to this, I completed two bachelors degrees (Engineering Physics and Applied Mathematics, 2015) at The University of Illinois at Urbana-Champaign. My undergraduate dissertation was titled Energy Storage in Quantum Resonators and was supervised by Professor Alfred Hรผbler within the Center for Complex Systems Research at UIUC.
This work ultimately resulted in a patent !!
[NOTE]: You can find a full list of my publications on my Google Scholar.
Intro to HPC Bootcamp: Engaging New Communities Through Energy Justice Projects
Journal of Computational Science, 2024Thorough Characterization and Analysis of Large Transformer Model Training At-Scale
Proc. ACM Meas. Anal. Comput. Syst. 03/2024MLMC: Machine Learning Monte Carlo for Lattice Gauge Theory
S. Foreman et al. Lattice, 2023 (Proceedings), 12/2023Protein Generation via Genome-scale Language Models with Bio-physical Scoring
@ SCโ23, 11/2023DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery [โฆ]
@ NeurIPS 2023 AI For Science Workshop, 10/2023Comprehensive Performance Study of LLMs on Novel AI Accelerators
M. Emani, S. Foreman, et al., IPDPS 2024, 10/2023Exploratory Analysis of Climate Data with
ClimRR
S. Foreman, Intro to HPC Bootcamp @ NERSC, 08/2023๐ GenSLMs: Genome-scale language models reveal SARS-Cov-2 evolutionary dynamics
@ SCโ22 10/2022Lattice QCD and Particle Physics
A.S. Kronfeld et al., 07/2022Applications of ML to Lattice QFT
D. Boyda, S. Calรญ, S. Foreman, et al., [arXiv:2202.05838], 02/2022LeapFrogLayers: Trainable Framework for Effective Sampling
S. Foreman, X.Y. Jin, J.C. Osborn, Lattice, 2021HMC with Normalizing Flows [slides]
S. Foreman et al., Lattice, 2021Deep Learning Hamiltonian Monte Carlo [+ poster]
S. Foreman, X.Y. Jin, & J.C. Osborn, @ SimDL Workshop @ ICLR, 2021Machine Learning and Neural Networks for Field Theory
S. Foreman, X.Y. Jin, & J.C. Osborn, SnowMass, 2020Examples of renormalization group transformations for image sets
S. Foreman et al., Physical Review E., 2018RG inspired Machine Learning for lattice field theory
S. Foreman et al., arXiv:1710.02079, 2017Large Energy Density in Three-Plate Nanocapacitors due to Coulomb Blockade
S. Foreman et al., J. Appl. Phys, 2018
Title | location | Date |
---|---|---|
Deep Learning and Foundation Models at Scale | ALCF Hands-on HPC Workshop | 2024-10-29 |
AuroraGPT | HPC User Forum Fall โ24 | 2024-09-04 |
Training LLMs at Scale | ATPESC 2024 | 2024-08-09 |
LLMs on Polaris | SciFM Summer School โ24 | 2024-07-17 |
MLMC: Machine Learning Monte Carlo | Lattice 2023 | 2023-07-31 |
๐ 2024
๐ 2023
๐ 2022
๐ 2021
๐ 2020
Title | Date |
---|---|
๐พ Converting Checkpoints | 2024-10-17 |
๐๏ธ Spike Skipper | 2024-09-17 |
๐ ezpz @ ALCF
|
2024-08-23 |
๐ How to Make Dope Slides | 2024-08-13 |
๐ฐ Deterministic flash-attn
|
2024-06-17 |
๐ธ flash-attn on Sunspot
|
2024-06-17 |
๐๏ธ Megatron-DeepSpeed on Intel XPU | 2024-06-15 |
๐ mpi4py bug on Sunspot
|
2024-05-25 |
๐ฒ MCMC + Diffusion Sampling | 2024-04-15 |
โฐ Starting Up Distributed Training on Aurora | 2024-03-21 |
๐ Loooooooong Sequence Lengths | 2024-02-12 |
l2hmc Example: 2D U(1)
|
2024-02-12 |
๐ข l2hmc-qcd Example: 2D U(1)
|
2023-12-14 |
๐ณ l2hmc-qcd Example: 4D SU(3)
|
2023-12-06 |
๐ช Events
Organizer for:
SC24 Workshop: High Performance Python for Science at Scale (HPPSS), November 2024
SC23 Workshop: High Performance Python for Science at Scale (HPPSS), November 2023
Machine Learning and Quantum Computing for Earth Sciences at 17th U. S. National Congress on Computational Mechanics, July 2023
๐ Employment
Position | @ | Start | End |
---|---|---|---|
Assistant Computational Scientist | ALCF | 2022 | โ |
Postdoc | ALCF | 2019 | 2022 |
Graduate Researcher | ANL | 2018 | 2019 |