High-Performance Computing

Also known as HPC

High-performance computing studies how to make large computations run efficiently on multicore CPUs, GPUs, and distributed clusters, supporting applications from scientific simulation to large-scale AI. Common approaches include parallel programming with MPI and OpenMP, GPU kernels and compiler optimization, and algorithms that reduce data movement and communication. Scheduling, load balancing, and collective communication help coordinate work across heterogeneous machines and facilities. A central challenge is scaling performance without sacrificing correctness, portability, or efficient use of memory and network resources.

Latest papers

143 papers10 papers in the last four weeks, down 41% on the four weeks before. 0.1% of all new papers.

Before the Ticket: Grounding HPC User Support in Documentation and Resolved Tickets with an Agentic LLM Assistant
Oct 21, 2026Elham J. Barezi, Primus C Kabuo, Niveditha NerellaQuestion Answering Document QA
Rosen Center for Advanced Computing, Purdue University, West Lafayette, IN, USA
SafeWall: A Risk-Aware Job Walltime Recommendation for HPC Scheduling
Oct 19, 2026Kanglin Xu, Michael Papka, Zhiling LanHigh-Performance Computing
University of Illinois Chicago, Chicago, IL, USA · Argonne National Laboratory, Lemont, IL, USA
Scalable long-range machine learning interatomic potentials with electrical response for atomistic material modeling
Oct 16, 2026Yicheng Chen, Xiaoyun Yu, Hyejeong Song +5Machine Learning Interatomic Potentials Computational Materials Science
Department of Materials Science and Engineering, National University of Singapore, Singapore · Department of Physics, National University of Singapore, Singapore
Data-Driven Prediction of Optimal MPI Rank Placement and Node Count for Memory-Bound CFD on AMD EPYC Clusters
Oct 16, 2026Marcin Lawenda, Łukasz Szustak, Aleksandra KrasickaHigh-Performance Computing Adaptive Rank Allocation
Poznan Supercomputing and Networking Center, Jana Pawła II 10, 61-139 Poznań, Poland · Czestochowa University of Technology, Dąbrowskiego 69, 42-201 Częstochowa, Poland
One Communicator, Three Vendors: Extending the MoA Predictive Theory to a Real NVIDIA+AMD+CPU MPI Ensemble
Oct 16, 2026Lenore Mullin, Gaetan HainsHigh-Performance Computing Heterogeneous Computing
College of Nanotechnology, Science and Engineering, University at Albany, SUNY, Albany, NY, USA · LACL, Université Paris-Est Créteil, Créteil, France
Deep Reinforcement Learning for HPC Job Scheduling: A Statistical Evaluation
Oct 14, 2026Justin M. Cheney, Clement N. NyirendaReinforcement Learning High-Performance Computing
Computer Science Department, University of the Western Cape, Robert Sobukwe Rd, Bellville, Cape Town, 7535, South Africa · eResearch Office, University of the Western Cape, Bellville, Cape Town, South Africa
REPORT-OPS: Hybrid Evidence-Guided Reporting with Human-Supervised Refinement for HPC
Oct 13, 2026Mah Kadidia Konate, Mayur Akewar, Janki Bhimani +1Evidence-Grounded Generation AI Agent Reliability
NERSC, Lawrence Berkeley National Laboratory, Berkeley, California, USA · Florida International University, Miami, Florida, USA
Reinforcement Learning-Guided Graph Transformations for SpTRSV Optimization
Sep 30, 2026Buse YılmazHigh-Performance Computing Sparse Matrix Multiplication
Department of Computer Engineering, MEF University, Huzur, Maslak Ayazağ̆a Cd., İstanbul, Turkey.
Purlin: Separating Orchestration from the Datapath of Collectives
Sep 29, 2026Osayamen Jonathan Aimuyo, Swapnil Gandhi, Christos KozyrakisLLM Inference Efficiency High-Performance Computing
Stanford University · NVIDIA & Stanford University
MegaGraph: Towards Efficient Training of Large-Scale Graph Transformers with Automated Hybrid Parallelism
Sep 28, 2026Tong Qiao, Ao Zhou, Yingjie Qi +2Distributed Optimization High-Performance Computing
School of Computer Science and Engineering, Beihang University, China · School of Software, Beihang University, China · State Key Laboratory of Complex and Critical Software Environment, Beihang University, China +1
Validating Memory-Optimal Transformer Kernels on Real Hardware: From Formal Derivation to Measured Performance Across Two HPC Clusters
Sep 27, 2026Lenore M. Mullin, Gaetan HainsGPU Kernel Optimization High-Performance Computing
Professor Emerita, College of Nanotechnology, Science, and Engineering, University at Albany (SUNY), Albany, NY, USA.
ASCEND: Personal AI Agents for Autonomous Scientific Computing Across HPC Clusters and GPU Workstations
Sep 26, 2026J. Paul Liu, Uthpala Herath, Andrew PetersenAI for Science High-Performance Computing
AI Hub for Science, College of Sciences, NC State University, Raleigh, NC · Research Computing and Support Services, Office of Information Technology, Duke University, Durham, NC · Office of Information Technology, NC State University, Raleigh, NC
Accelerating Sharded Data Parallelism at Scale with Federated Learning
Sep 17, 2026Gianluca Mittone, Marco AldinucciCommunication-Efficient Distributed Training High-Performance Computing
University of Turin, Turin, Italy
The Life of a Token: from Words to Bits on the Wire
Sep 17, 2026Davide Avesani, Pengwenlong Gu, Sotiris Skaperas +1Communication-Efficient Distributed Training High-Performance Computing
CEDRIC - ROC · Cnam
Detecting Soft Errors in Parallel Software with LLM-tuned Instruction Duplication
Sep 17, 2026Yafan Huang, Guanpeng LiHigh-Performance Computing
University of Iowa Iowa City, IA, USA · University of Florida Gainesville, FL, USA
COMPASS-ABS: Reducing Fragmentation in Shared GPU Clusters for Deep Learning Training Workloads
Sep 16, 2026Yukai Zhou, Hongfan WuHigh-Performance Computing
High-Performance Tensor Formulation of the Viterbi Algorithm for Hidden Semi-Markov Models
Sep 15, 2026Lorenzo Piarulli, Elia Belli, Daniele De SensiMarkov Models High-Performance Computing
Department of Computer Science Sapienza University of Rome
Accelerating Transfer-Learning-Based Autotuning with Predictive LLVM IR Performance Ranking
Sep 14, 2026Md Arafat Hossain, Thomas Randall, Akash Dutta +3Learning to Rank High-Performance Computing
School of Computing Clemson University Clemson, South Carolina, USA · MCS Argonne National Laboratory Lemont, Illinois, USA
Hyperion: An AI-powered HPC cluster for sciences and humanities research that utilizes ML for predicting job turnaround time
Sep 14, 2026Jun Zhou, Nathan Elgar, Tawnee Benedetto +5High-Performance Computing
University of South Carolina Columbia, South Carolina, USA · University of South Carolina Columbia, USA · Boston University Boston, USA
Leakage-Safe and Scheduler-Aware Machine Learning for Grid Job Runtime Prediction
Sep 12, 2026Ashfaq Ali Shafin, Khandaker Mamun AhmedHigh-Performance Computing
Augustana College, USA · Florida International University, USA · Dakota State University, USA
4D Parallelism Unlocks Exascale Bayesian Neural Networks for High-Fidelity Atmospheric Modeling
Sep 11, 2026Deifilia Kieckhefen, Juan Pedro Gutiérrez Hermosillo Muriedas, Lars Helge Heyen +12Bayesian Neural Networks Uncertainty Quantification
Karlsruhe Institute of Technology, Germany · Forschungszentrum Jülich, Germany · CSC – IT Center for Science Ltd., Finnland +1
Fidelity-Aware Scheduling of Quantum Circuits on Multi-QPU Systems
Sep 9, 2026Innocenzo Fulginiti, Antonio Tudisco, Salvatore Zammuto +7High-Performance Computing Heterogeneous Computing
Technical University of Munich, Munich, Germany · Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy · MQSC, Garching near Munich, Germany +1
Scalability Analysis of Distributed Kolmogorov-Arnold Network Training on High-Performance Computing Systems
Sep 7, 2026Guangneng Chen, David Garcia Selfa, Pablo Quesada BarriusoHigh-Performance Computing Kolmogorov-Arnold Networks
University of Santiago de Compostela, 15782 Santiago de Compostela, Spain · Galicia Supercomputing Center (CESGA), 15705 Santiago de Compostela, Spain
Agentic Algorithm Engineering: Improving Shared-Memory Exact Minimum Cuts
Sep 7, 2026David A. Bader, Adil Chhabra, Ernestine Großmann +3High-Performance Computing Combinatorial Optimization
New Jersey Institute of Technology, Newark, NJ, USA · Heidelberg University, Heidelberg, Germany. · Institute of Science and Technology Austria (ISTA), Klosterneuburg, Austria +1
Diamond Agent: Agentic Control of Federated HPC Resources as a Service
Sep 5, 2026Haotian Xie, Junlin Chen, Mingkai Zheng +9High-Performance Computing Agentic Workflows
Rutgers University · University of Rochester · National Center for Supercomputing Applications +3
From Splats to Silicon: Rethinking Computational Efficiency of 3DGS
Sep 5, 2026Minnan Pei, Qiwei Dong, Yihan Zhou +73D Gaussian Splatting 3DGS Acceleration
Institute of Automation, Chinese Academy of Sciences, and also with the University of Chinese Academy of Sciences · Nanjing University · Eindhoven University of Technology +1
Towards Efficient Evaluation of Evolutionary Transfer Optimization: Case Studies on Task-Parameterized Applications
Sep 4, 2026Yanchen Li, Xiaoming Xue, Kay Chen TanEvolutionary Optimization Multi-Task Optimization
Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University, Hong Kong SAR, China · School of Petroleum Engineering, China University of Petroleum (East China), Qingdao, China
Spectral Analysis for Sparse Matrix Computation: Insights and Potential
Aug 29, 2026Ruifeng Zhang, Xipeng ShenSparse Matrix Multiplication High-Performance Computing
North Carolina State University Raleigh, North Carolina, USA
Maia 200: A Software Defined Dataflow System for Large-scale AI Acceleration
Aug 25, 2026Sherry Xu, Marco Heddes, Jackson Peng +14AI Accelerator Inference High-Performance Computing
Microsoft Corporation
Trust, but Verify: Rigorously Profiling Best-Effort High-Performance Computing for Digital Evolution
Aug 25, 2026Matthew Andres Moreno, Santiago Rodriguez Papa, Charles Ofria +2High-Performance Computing
Department of Ecology and Evolutionary Biology; Center for the Study of Complex Systems; University of Michigan, Ann Arbor, MI, USA · Department of Computer Science and Engineering; Program in Ecology, Evolution, and Behavior; Michigan State University, East Lansing, MI, USA

Oct 21, 2026J/K move · Enter open · S save

Before the Ticket: Grounding HPC User Support in Documentation and Resolved Tickets with an Agentic LLM Assistant

Elham J. Barezi, Primus C Kabuo, Niveditha Nerella

Rosen Center for Advanced Computing, Purdue University, West Lafayette, IN, USA

Question Answering Document QA LLM Tool Use High-Performance Computing Retrieval-Augmented Generation

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Most questions that reach an HPC help desk have already been answered in the center's user guides or in a ticket someone else filed last semester; users still file new tickets because the guides are hard to navigate and the ticket history is not theirs to search. We present an assistant that answers from both sources: an orchestrator calls two tools over the Model Context Protocol, retrieval-augmented generation (RAG) over the live documentation and a Llama-3-8B model fine-tuned with QLoRA on 11,244 query-resolution pairs mined from historical tickets, and merges their answers. Every model runs on-premises or on the university's hosted LLM service because ticket data may not leave the institution. On 400 held-out tickets from Purdue's Rosen Center for Advanced Computing, disjoint from training and free of near-duplicates, and evaluated by two judges from model families that generated none of the answers, fine-tuning on resolutions rewritten into self-service guidance is the clear winner in agreement with RCAC's resolutions (BERTScore F1 improves from 0.06 to 0.27 over the base model) and is judged most correct on average. The end-to-end system does not improve on its tools, although they are complementary: choosing the better answer per question would exceed either tool (judged correctness 3.41 versus 3.20, an oracle bound), while the merge follows the documentation tool in 78% of answers. Returning one tool's answer instead recovers the fine-tuned tool's quality (3.19 versus 2.66), but neither a learned selector nor an LLM verifier beats that tool alone.