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The rapid scaling of large language model (LLM) training and inference has driven their adoption in semiconductor design across academia and industry. While most prior work evaluates LLMs on hardware description language (HDL) tasks,…

Hardware Architecture · Computer Science 2025-10-27 Stefan Abi-Karam , Cong Hao

This paper investigates an emerging cache side channel attack defense approach involving the use of hardware performance counters (HPCs). These counters monitor microarchitectural events and analyze statistical deviations to differentiate…

Cryptography and Security · Computer Science 2023-12-18 William Kosasih

Recent advancements in ultra-low-power machine learning (TinyML) hardware promises to unlock an entirely new class of smart applications. However, continued progress is limited by the lack of a widely accepted benchmark for these systems.…

Cloud service providers commonly use standard benchmarks like TPC-H and TPC-DS to evaluate and optimize cloud data analytics systems. However, these benchmarks rely on fixed query patterns and fail to capture the real execution statistics…

The Discrete Event System Specification formalism (DEVS), which supports hierarchical and modular model composition, has been widely used to understand, analyze and develop a variety of systems. DEVS has been implemented in various…

Performance · Computer Science 2024-02-09 José L. Risco-Martín , Saurabh Mittal , Juan Carlos Fabero , Marina Zapater , Román Hermida

High-Performance Computing (HPC) platforms enable scientific software to achieve breakthroughs in many research fields such as physics, biology, and chemistry, by employing Research Software Engineering (RSE) techniques. These include 1)…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-10-16 Matan Rusanovsky , Re'em Harel , Lee-or Alon , Idan Mosseri , Harel Levin , Gal Oren

In the last year, new models and methods for pretraining and transfer learning have driven striking performance improvements across a range of language understanding tasks. The GLUE benchmark, introduced a little over one year ago, offers a…

Computation and Language · Computer Science 2020-02-14 Alex Wang , Yada Pruksachatkun , Nikita Nangia , Amanpreet Singh , Julian Michael , Felix Hill , Omer Levy , Samuel R. Bowman

Large language models (LLMs) are being increasingly integrated into practical hardware and firmware development pipelines for code generation. Existing studies have primarily focused on evaluating the functional correctness of LLM-generated…

Cryptography and Security · Computer Science 2026-01-21 Qirui Chen , Jingxian Shuai , Shuangwu Chen , Shenghao Ye , Zijian Wen , Xufei Su , Jie Jin , Jiangming Li , Jun Chen , Xiaobin Tan , Jian Yang

Field-Programmable Gate Arrays (FPGAs) are widely used in modern hardware design, yet writing Hardware Description Language (HDL) code for FPGA implementation remains a complex and time-consuming task. Large Language Models (LLMs) have…

Hardware Architecture · Computer Science 2025-03-25 Ce Guo , Tong Zhao

Evaluating competing systems in a comparable way, i.e., benchmarking them, is an undeniable pillar of the scientific method. However, system performance is often summarized via a small number of metrics. The analysis of the evaluation…

Machine Learning · Computer Science 2025-10-24 Quannian Zhang , Michael Röder , Nikit Srivastava , N'Dah Jean Kouagou , Axel-Cyrille Ngonga Ngomo

The LHCb experiment at CERN is undergoing an upgrade in preparation for the Run 3 data taking period of the LHC. As part of this upgrade the trigger is moving to a fully software implementation operating at the LHC bunch crossing rate. We…

Instrumentation and Detectors · Physics 2022-01-06 R. Aaij , M. Adinolfi , S. Aiola , S. Akar , J. Albrecht , M. Alexander , S. Amato , Y. Amhis , F. Archilli , M. Bala , G. Bassi , L. Bian , M. P. Blago , T. Boettcher , A. Boldyrev , S. Borghi , A. Brea Rodriguez , L. Calefice , M. Calvo Gomez , D. H. Cámpora Pérez , A. Cardini , M. Cattaneo , V. Chobanova , G. Ciezarek , X. Cid Vidal , J. L. Cobbledick , J. A. B. Coelho , T. Colombo , A. Contu , B. Couturier , D. C. Craik , R. Currie , P. d'Argent , M. De Cian , D. Derkach , F. Dordei , M. Dorigo , L. Dufour , P. Durante , A. Dziurda , A. Dzyuba , S. Easo , S. Esen , P. Fernandez Declara , S. Filippov , C. Fitzpatrick , M. Frank , P. Gandini , V. V. Gligorov , E. Golobardes , G. Graziani , L. Grillo , P. A. Günther , S. Hansmann-Menzemer , A. M. Hennequin , L. Henry , D. Hill , S. E. Hollitt , J. Hu , W. Hulsbergen , R. J. Hunter , M. Hushchyn , B. K. Jashal , C. R. Jones , S. Klaver , K. Klimaszewski , R. Kopecna , W. Krzemien , M. Kucharczyk , R. Lane , F. Lazzari , R. Le Gac , P. Li , J. H. Lopes , M. Lucio Martinez , A. Lupato , O. Lupton , X. Lyu , F. Machefert , O. Madejczyk , S. Malde , J. F. Marchand , S. Mariani , C. Marin Benito , D. Martinez Santos , F. Martinez Vidal , R. Matev , M. Mazurek , B. Mitreska , D. S. Mitzel , M. J. Morello , H. Mu , P. Muzzetto , P. Naik , M. Needham , N. Neri , N. Neufeld , N. S. Nolte , D. O'Hanlon , A. Oyanguren , M. Pepe Altarelli , S. Petrucci , M. Petruzzo , L. Pica , F. Pisani , A. Piucci , F. Polci , A. Poluektov , E. Polycarpo , C. Prouve , G. Punzi , R. Quagliani , R. I. Rabadan Trejo , M. Ramos Pernas , M. S. Rangel , F. Ratnikov , G. Raven , F. Reiss , V. Renaudin , P. Robbe , A. Ryzhikov , M. Santimaria , M. Saur , M. Schiller , R. Schwemmer , B. Sciascia , A. Solomin , F. Suljik , N. Skidmore , M. D. Sokoloff , P. Spradlin , M. Stahl , S. Stahl , H. Stevens , L. Sun , A. Szabelski , T. Szumlak , M. Szymanski , D. Y. Tou , G. Tuci , A. Usachov , N. Valls Canudas , R. Vazquez Gomez , S. Vecchi , M. Vesterinen , X. Vilasis-Cardona , D. Vom Bruch , Z. Wang , T. Wojton , M. Whitehead , M. Williams , M. Witek , Y. Xie , A. Xu , H. Yin , M. Zdybal , O. Zenaiev , D. Zhang , L. Zhang , X. Zhu

The rise of big data systems has created a need for benchmarks to measure and compare the capabilities of these systems. Big data benchmarks present unique scalability challenges. The supercomputing community has wrestled with these…

Performance · Computer Science 2016-12-13 Patrick Dreher , Chansup Byun , Chris Hill , Vijay Gadepally , Bradley Kuszmaul , Jeremy Kepner

The paradigm shift towards multi-core and heterogeneous computing, driven by the fundamental power and thermal limits of single-core processors, has established energy efficiency as a first-class design constraint in high-performance…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-30 Mufakir Qamar Ansari , Mudabir Qamar Ansari

Parallel programs in high performance computing (HPC) continue to grow in complexity and scale in the exascale era. The diversity in hardware and parallel programming models make developing, optimizing, and maintaining parallel software…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-15 Daniel Nichols , Aniruddha Marathe , Harshitha Menon , Todd Gamblin , Abhinav Bhatele

High-performance computing (HPC) has evolved over decades through multiple architectural transitions, from vector supercomputers to massively parallel CPU clusters and GPU-accelerated systems, continuously expanding the frontier of…

Quantum Physics · Physics 2026-04-23 Suman Raj , Siva Sai , Yogesh Simmhan , Kyle Chard , Rajkumar Buyya

The past few years have seen a surge of applying Deep Learning (DL) models for a wide array of tasks such as image classification, object detection, machine translation, etc. While DL models provide an opportunity to solve otherwise…

Machine Learning · Computer Science 2021-03-02 Cheng Li , Abdul Dakkak , Jinjun Xiong , Wen-mei Hwu

The increasing demands for computing performance have been a reality regardless of the requirements for smaller and more energy efficient devices. Throughout the years, the strategy adopted by industry was to increase the robustness of a…

Software Engineering · Computer Science 2019-05-07 Hugo Andrade , Ivica Crnkovic

Interest in parallel architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of Graphic Processing Units (GPUs) and Intel Many Integrated Core…

Instrumentation and Detectors · Physics 2014-11-26 S. Amerio , D. Bastieri , M. Corvo , A. Gianelle , W. Ketchum , T. Liu , A. Lonardo , D. Lucchesi , S. Poprocki , R. Rivera , L. Tosoratto , P. Vicini , P. Wittich

In recent years, language models (LMs), such as GPT-4, have been widely used in multiple domains, including natural language processing, visualization, and so on. However, applying them for analyzing and optimizing high-performance…

Machine Learning · Computer Science 2023-11-28 Le Chen , Pei-Hung Lin , Tristan Vanderbruggen , Chunhua Liao , Murali Emani , Bronis de Supinski

As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these systems rises. Considering the broad use of big data…