Harshitha is a Computer Scientist at the Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory. She joined CASC as a postdoctoral research staff in 2016. Her research focuses on Large Language Models (LLMs) and Machine Learning for HPC code development, Approximate Computing, and floating-point mixed-precision analysis.

Harshitha received her Ph.D. in 2016 and M.S. in 2012, both from the University of Illinois at Urbana-Champaign. She is a recipient of the ACM/IEEE-CS George Michael Fellowship in 2014, the Anita Borg Scholarship in 2014 and the Siebel Scholarship in 2012.

Please find more information at her personal website. This website is not sanctioned, affiliated, or supported by LLNL or DOE.

Ph.D. Computer Science, University of Illinois at Urbana Champaign

For the full list of publications please visit my Google scholar page

• MLeveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions.
  Keita Teranishi, Harshitha Menon, William Godoy, et al.
  [LLM4HPC 2025 co-located with ISC]
• Can Large Language Models Predict Parallel Code Performance?
  Gregory Bolet, Giorgis Georgakoudis, Harshitha Menon, Konstantinos Parasyris, Niranjan Hasabnis, Hayden Estes, Kirk W Cameron, Gal Oren
  [AI4Sys 2025 co-located with HPDC]
• HPAC-ML: A Programming Model for Embedding ML Surrogates in Scientific Applications.
  Zane Fink, Konstantinos Parasyris, Praneet Rathi, Giorgis Georgakoudis, Harshitha Menon, Peer-Timo Bremer.
  [SC 2024]
• A taxonomy of automatic differentiation pitfalls.
  Jan Hückelheim, Harshitha Menon, William Moses, Bruce Christianson, Paul Hovland, Laurent Hascoët.
  [WIREs Data Mining and Knowledge Discovery 2024]

• Modeling parallel programs using large language models.
  Daniel Nichols, Aniruddha Marathe, Harshitha Menon, Todd Gamblin, Abhinav Bhatele.
  [ISC 2024]
• Learning to Predict and Improve Build Successes in Package Ecosystems.
  Harshitha Menon*, Daniel Nichols*, Abhinav Bhatele, Todd Gamblin.
  [MSR 2024]
• HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU.
  Zane Fink, Konstantinos Parasyris, Giorgis Georgakoudis, Harshitha Menon.
  [SC 2023]
• A Short Review of Automatic Differentiation Pitfalls in Scientific Computing.
  Jan Hueckelheim, Harshitha Menon, William S Moses, Bruce Christianson, Paul Hovland, Laurent Hascoet.
  [ICML Workshop 2023]
• Approximate High-Performance Computing: A Fast and Energy-Efficient Computing Paradigm in the Post-Moore Era.
  Harshitha Menon, James Diffenderfer, Giorgis Georgakoudis, Ignacio Laguna, Michael O Lam, Daniel Osei-Kuffuor, Konstantinos Parasyris, Jackson Vanover.
  [IT-PRO 2023]
• Approximate computing through the lens of uncertainty quantification.
  Konstantinos Parasyris, James Diffenderfer, Harshitha Menon, Ignacio Laguna, Jackson Vanover, Ryan Vogt, Daniel Osei-Kuffuor.
  [SC 2022]
• A visual comparison of silent error propagation.
  Zhimin Li, Harshitha Menon, Kathryn Mohror, Shusen Liu, Luanzheng Guo, Peer-Timo Bremer, Valerio Pascucci.
  [TVCG 2022]
• Searching for High Fidelity Builds Using Active Learning.
  Harshitha Menon*, Konstantinos Parasyris*, Todd Gamblin, Tom Scogland.
  [MSR 2021]
• HPAC: evaluating approximate computing techniques on HPC OpenMP applications.
  Konstantinos Parasyris,Giorgis Georgakoudis, Harshitha Menon, James Diffenderfer, Ignacio Laguna, Daniel Osei-Kuffuor, Markus Schordan.
  [SC 2021]
• QDOT: Quantized dot product kernel for approximate high-performance computing.
  James Diffenderfer, Daniel Osei-Kuffuor, Harshitha Menon.
  [SISC 2021]
• Understanding a program's resiliency through error propagation.
  Zhimin Li, Harshitha Menon,Kathryn Mohror, Peer-Timo Bremer, Yarden Livant, Valerio Pascucci.
  [PPoPP 2021]
• Auto-tuning parameter choices in HPC applications using Bayesian optimization.
  Harshitha Menon, Abhinav Bhatele, Todd Gamblin.
  [IPDPS 2020]
• Spotsdc: Revealing the silent data corruption propagation in high-performance computing systems.
  Zhimin Li, Harshitha Menon, Dan Maljovec, Yarden Livnat, Shusen Liu, Kathryn Mohror, Peer-Timo Bremer, Valerio Pascucci.
  [TVCG 2020]
• Algorithmic differentiation applied to floating-point precision tuning.
  Harshitha Menon, Michael Lam, Daniel Osei-Kuffuor, Markus Schordan, Scott Lloyd, Kathryn Mohror, and Jeffrey Hittinger.
  [SC 2018]
• Discvar: discovering critical variables using algorithmic differ- entiation for transient faults.
  Harshitha Menon and Kathryn Mohror.
  [PPoPP 2018]
• Multi-level load balancing with an integrated runtime approach.
  Seonmyeong Bak,Harshitha Menon, Sam White, Matthias Diener, and Laxmikant Kale.
  [CCGRID 2018]
• Power, reliability, and performance: One system to rule them all.
  Bilge Acun, Akhil Langer, Esteban Meneses, Harshitha Menon, Osman Sarood, Ehsan Totoni, and Laxmikant V. Kalé.
  [IEEE Computer 2016]
• Adaptive Techniques for Clustered N-Body Cosmological Simulations
  Harshitha Menon, Lukasz Wesolowski, Gengbin Zheng, Pritish Jetley, Laxmikant Kale, Thomas Quinn, Fabio Governato
  [Computational Astrophysics and Cosmology 2015]
• All about baryons: revisiting sidm predictions at small halo masses.
  A Bastidas Fry, F Governato, A Pontzen, T Quinn, M Tremmel, L Anderson,H Menon, AM Brooks, and J Wadsley.
  [Monthly Notices of the Royal Astronomical Society 2015]
• Scalable Replay with Partial-Order Dependencies for Message-Logging Fault Tolerancen
  Jonathan Lifflander, Esteban Meneses, Harshitha Menon, Phil Miller, Sriram Krishnamoorthy, Laxmikant Kale
  [CLUSTER 2014] BEST STUDENT PAPER AWARD
• Parallel Programming with Migratable Objects: Charm++ in Practice
  Bilge Acun, Abhishek Gupta, Nikhil Jain, Akhil Langer, Harshitha Menon, Eric Mikida , Xiang Ni, Michael Robson, Yanhua Sun, Ehsan Totoni, Lukasz Wesolowski, Laxmikant Kale
  [SC 2014]
• A Distributed Dynamic Load Balancer for Iterative Applications
  Harshitha Menon, Laxmikant Kale
  [SC 2013] BEST STUDENT PAPER FINALIST
• Migratable Objects + Active Messages + Adaptive Runtime = Productivity + Performance: A Submission to the 2012 HPC Class II Challenge
  Laxmikant Kale, Anshu Arya, Nikhil Jain, Akhil Langer, Jonathan Lifflander, Harshitha Menon, Xiang Ni, Yanhua Sun, Ehsan Totoni, Ramprasad Venkataraman, Lukasz Wesolowski
  [SC 2012] HPC Class II Challenge

• SC21 Best Reproducibility Award Winner.
• ACM/IEEE-CS George Michael Memorial HPC Fellowship, SC ’14.
• Best Student Paper at Cluster 2014. Scalable Replay with Partial-Order Dependencies for Message-Logging Fault Tolerance; Lifflander et al.
• Best Student Paper finalist at SC 2013. A Distributed Dynamic Load Balancer for Iterative Applications; Harshitha Menon, Laxmikant Kale .
• Google Anita Borg Scholarship - 2014.
• Awarded Siebel Scholarship Class of 2012 - The Siebel Scholars Foundation rewards excellence among the top students at the leading graduate schools.
• Awarded Google Fellowship for Employees, 2010 - Competitive fellowship granted to Google employees.
• Awarded Founders Award at Google in 2007 for contribution to Gmail.