Welcome! I'm a 3rd year computer science PhD student at Stanford University, advised by Fred Kjolstad.
I'm interested in high-performance computing, domain-specific languages, and GPUs. I'm grateful to be funded by an NSF Graduate Research Fellowship.
I graduated from Berkeley in 2015, where I double majored in Computer Science and Applied Mathematics.
Before Stanford I spent 4 years as a GPU and ML engineer:
first at Lawrence Livermore National Laboratory building parallel & scalable physics software for GPU-based supercomputers. My code was the computational heart of 15,000-GPU simulation of a human cell's lipid bilayer, and is still used by the National Cancer Instute.
After that I spent 2 years at Cruise as a senior engineer working on autonomous vehicles.
Compiling Recurrences to Dense and Sparse Arrays
Shiv Sundram, Muhammmed Usman Tariq, Fredrik Kjolstad
To appear in Proceedings of the ACM on Programming Languages, October 2024 [Preprint]
A Massively Parallel Infrastructure for Adaptive Multiscale Simulations: Modeling RAS Initiation Pathway for Cancer
Francesco Di Natale, Harsh Bhatia, Timothy S Carpenter, Chris Neale, Sara Kokkila-Schumacher, Tomas Oppelstrup, Liam Stanton, Xiaohua Zhang, Shiv Sundram, Thomas RW Scogland, Gautham Dharuman, Michael P Surh, Yue Yang, Claudia Misale, Lars Schneidenbach, Carlos Costa, Changhoan Kim, Bruce D'Amora, Sandrasegaram Gnanakaran, Dwight V Nissley, Fred Streitz, Felice C Lightstone, Peer-Timo Bremer, James N Glosli, Helgi I Ingólfsson
ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC), November 2019 (SC 19)
[Paper]
Best Paper Award, Supercomputing 2019
ddcMD: A Fully GPU-accelerated Molecular Dynamics Program for the Martini Force Field
Xiaohua Zhang, Shiv Sundram, Tomas Oppelstrup, Sara IL Kokkila-Schumacher, Timothy S Carpenter, Helgi I Ingólfsson, Frederick H Streitz, Felice C Lightstone, James N Glosli
The Journal of Chemical Physics, July 2020 [Paper]
Task Fusion in Distributed Runtimes
Shiv Sundram, Wonchan Lee, Alex Aiken
2022 IEEE/ACM 5th Annual Parallel Applications Workshop: Alternatives To MPI+ X (PAW-ATM 22)
[Paper]
Machine Learning–driven Multiscale Modeling Reveals Lipid-dependent Dynamics of RAS Signaling Proteins
Helgi I Ingólfsson, Chris Neale, Timothy S Carpenter, Rebika Shrestha, Cesar A López, Timothy H Tran, Tomas Oppelstrup, Harsh Bhatia, Liam G Stanton, Xiaohua Zhang, Shiv Sundram, Francesco Di Natale, Animesh Agarwal, Gautham Dharuman, Sara IL Kokkila Schumacher, Thomas Turbyville, Gulcin Gulten, Que N Van, Debanjan Goswami, Frantz Jean-Francois, Constance Agamasu, De Chen, Jeevapani J Hettige, Timothy Travers, Sumantra Sarkar, Michael P Surh, Yue Yang, Adam Moody, Shusen Liu, Brian C Van Essen, Arthur F Voter, Arvind Ramanathan, Nicolas W Hengartner, Dhirendra K Simanshu, Andrew G Stephen, Peer-Timo Bremer, S Gnanakaran, James N Glosli, Felice C Lightstone, Frank McCormick, Dwight V Nissley, Frederick H Streitz
Proceedings of the National Academy of Sciences, January 2022 [Paper]
Revet: A Language and Compiler for Dataflow Threads
Alexander Rucker, Shiv Sundram, Coleman Smith, Matthew Vilim, Raghu Prabhakar, Fredrik Kjolstad, Kunle Olukotun
High Performance Computer Architecture, March 2024 [Paper]
Machine Learning Algorithms for Automated NIF Capsule Mandrel Selection
K-J Boehm, Y Ayzman, R Blake, A Garcia, K Sequoia, S Sundram, W Sweet
Fusion Science and Technology, August 2020 [Paper]
Preparation and Optimization of a Diverse Workload for a Large-scale Heterogeneous System
Ian Karlin et al.
ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC), November 2019 (SC 19)
[Paper]
Industry work
Cruise
Senior Software Engineer
March 2019 - Aug 2020
Lawrence Livermore National Laboratory (LLNL)
Scientific Software Developer & Researcher
Aug 2016 - Feb 2019
Microsoft
Software Engineer
Dec 2016 - Aug 2016
Qualcomm Research
Research Intern
Summer 2015
Other Presentations
Scaling molecular dynamics to 25,000 GPU’s on Sierra and Summit
Shiv Sundram, Tomas Oppelstrup
Nvidia GPU Technology Conference 2018, San Jose CA
[slides]
Contact
For professional communications, you are welcome to use my current
academic address, shiv1@stanford.edu.
