{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T06:21:28Z","timestamp":1769754088889,"version":"3.49.0"},"reference-count":51,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,9,23]],"date-time":"2024-09-23T00:00:00Z","timestamp":1727049600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,9,23]],"date-time":"2024-09-23T00:00:00Z","timestamp":1727049600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100005005","name":"Ben-Gurion University of the Negev","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005005","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100002418","name":"Intel Corporation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100002418","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009327","name":"Pazy Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100009327","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,9,23]]},"DOI":"10.1109\/hpec62836.2024.10938441","type":"proceedings-article","created":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T19:07:19Z","timestamp":1743707239000},"page":"1-7","source":"Crossref","is-referenced-by-count":2,"title":["MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks"],"prefix":"10.1109","author":[{"given":"Tal","family":"Kadosh","sequence":"first","affiliation":[{"name":"Ben-Gurion University"}]},{"given":"Niranjan","family":"Hasabnis","sequence":"additional","affiliation":[{"name":"Code Metal"}]},{"given":"Vy A.","family":"Vo","sequence":"additional","affiliation":[{"name":"Intel Labs"}]},{"given":"Nadav","family":"Schneider","sequence":"additional","affiliation":[{"name":"Ben-Gurion University"}]},{"given":"Neva","family":"Krien","sequence":"additional","affiliation":[{"name":"Ben-Gurion University"}]},{"given":"Mihai","family":"Capot\u0103","sequence":"additional","affiliation":[{"name":"Intel Labs"}]},{"given":"Abdul","family":"Wasay","sequence":"additional","affiliation":[{"name":"Intel Labs"}]},{"given":"Guy","family":"Tamir","sequence":"additional","affiliation":[{"name":"Intel"}]},{"given":"Ted","family":"Willke","sequence":"additional","affiliation":[{"name":"Intel Labs"}]},{"given":"Nesreen","family":"Ahmed","sequence":"additional","affiliation":[{"name":"Intel Labs"}]},{"given":"Yuval","family":"Pinter","sequence":"additional","affiliation":[{"name":"Ben-Gurion University"}]},{"given":"Timothy","family":"Mattson","sequence":"additional","affiliation":[{"name":"Ben-Gurion University"}]},{"given":"Gal","family":"Oren","sequence":"additional","affiliation":[{"name":"Technion"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Recent advances in natural language processing via large pretrained language models: A survey","author":"Min","year":"2021","journal-title":"ACM Computing Surveys"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s11023-020-09548-1"},{"key":"ref3","article-title":"Sparks of artificial general intelligence: Early experiments with gpt-4","author":"Bubeck","year":"2023","journal-title":"arXiv preprint"},{"key":"ref4","article-title":"OpenAI ChatGPT","volume-title":"OpenAI","year":"2023"},{"key":"ref5","article-title":"Reinventing high performance computing: challenges and opportunities","author":"Reed","year":"2022","journal-title":"arXiv preprint"},{"key":"ref6","article-title":"HPC: Where we are today and a look into the future","volume-title":"Parallel Processing and Applied Mathematics, PPAM: Gdansk, Poland","author":"Dongarra","year":"2022"},{"issue":"2","key":"ref7","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1145\/3552309","article-title":"HPC Forecast: Cloudy and Uncertain","volume":"66","author":"Reed","year":"2023","journal-title":"Communications of the ACM"},{"key":"ref8","article-title":"LM4HPC: Towards Effective Language Model Application in High-Performance Computing","author":"Chen","year":"2023","journal-title":"arXiv preprint"},{"key":"ref9","article-title":"Learning to Parallelize with OpenMP by Augmented Heterogeneous AST Representation","volume-title":"Proceedings of Machine Learning and Systems","volume":"5","author":"Chen"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3572848.3582565"},{"key":"ref11","article-title":"PragFormer: Data-driven Parallel Source Code Classification with Transformers","author":"Kadosh","year":"2023","journal-title":"arXiv"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-40744-4_1"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.23919\/isc.2024.10528929"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3624062.3624063"},{"issue":"9","key":"ref15","doi-asserted-by":"crossref","first-page":"e7648","DOI":"10.1002\/cpe.7648","article-title":"Multigraph learning for paral-lelism discovery in sequential programs","volume":"35","author":"Shen","year":"2023","journal-title":"Concurrency and Computation: Practice and Experience"},{"key":"ref16","article-title":"Position Paper: The Landscape and Challenges of HPC Research and LLMs","volume-title":"arXiv preprint","author":"Chen","year":"2024"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s10766-019-00640-3"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-90539-2_16"},{"key":"ref19","first-page":"247","article-title":"ComPar: optimized multi-compiler for automatic OpenMP S2S parallelization","volume-title":"OpenMP: Portable Multi-Level Parallelism on Modern Systems: 16th International Workshop on OpenMp, IWOMP 2020, Austin, TX, USA, September 22\u201324, 2020, Proceedings 16","author":"Mosseri"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/PARCOMPTECH.2017.8068329"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.5168"},{"key":"ref22","article-title":"Large Language Models for Software Engineering: A Systematic Literature Review","author":"Hou","year":"2023","journal-title":"arXiv preprint"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3625549.3658689"},{"key":"ref24","first-page":"1","article-title":"A systematic evaluation of large language models of code","volume-title":"Proceedings of the 6th ACM SIGPLAN International Symposium on Machine Programming","author":"Xu"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3624062.3624172"},{"key":"ref26","article-title":"AUTOPARLLM: GNN-Guided Automatic Code Parallelization using Large Language Models","author":"Mahmud","year":"2023","journal-title":"arXiv preprint"},{"key":"ref27","author":"Kadosh","year":"2023","journal-title":"Quantifying openmp: Statistical insights into usage and adoption"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1145\/3432261.3432263","article-title":"An analysis of system balance and architectural trends based on top500 supercomputers","volume-title":"The International Conference on High Performance Computing in Asia-Pacific Region","author":"Khan","year":"2021"},{"key":"ref29","article-title":"Codexglue: A machine learning benchmark dataset for code understanding and generation","author":"Lu","year":"2021","journal-title":"arXiv preprint"},{"key":"ref30","article-title":"Gpt-neo: Large scale autoregressive language modeling with mesh-tensorflow","volume":"58","author":"Black","year":"2021","journal-title":"If you use this software, please cite it using these metadata"},{"key":"ref31","author":"Wang","year":"2021","journal-title":"Gpt-j-6b: A 6 billion parameter autoregressive language model"},{"key":"ref32","article-title":"Evaluating large language models trained on code","author":"Chen","year":"2021","journal-title":"arXiv preprint"},{"key":"ref33","article-title":"Starcoder: may the source be with you","author":"Li","year":"2023","journal-title":"arXiv preprint"},{"key":"ref34","article-title":"Gpt-neox-20b: An open-source autoregressive language model","author":"Black","year":"2022","journal-title":"arXiv preprint"},{"key":"ref35","volume-title":"GPT-NeoX: Large Scale Autoregressive Language Modeling in PyTorch","author":"Andonian","year":"2023"},{"key":"ref36","article-title":"What do code models memorize? an empirical study on large language models of code","author":"Yang","year":"2023","journal-title":"arXiv preprint"},{"key":"ref37","article-title":"Neural machine translation of rare words with subword units","author":"Sennrich","year":"2015","journal-title":"arXiv preprint"},{"key":"ref38","article-title":"Code means more than plain language: Bringing syntax structure awareness to algorithmic problem solution generation","author":"Zheng","year":"2022","journal-title":"arXiv"},{"key":"ref39","article-title":"A survey on pretrained language models for neural code intelligence","author":"Xu","year":"2022","journal-title":"arXiv preprint"},{"key":"ref40","article-title":"Codetf: One-stop transformer library for state-of-the-art code llm","author":"Bui","year":"2023","journal-title":"arXiv preprint"},{"key":"ref41","article-title":"Neural machine translation for code generation","author":"KC","year":"2023","journal-title":"arXiv preprint"},{"key":"ref42","article-title":"Codebleu: a method for automatic evaluation of code synthesis","volume-title":"arXiv preprint","author":"Ren","year":"2020"},{"key":"ref43","first-page":"311","article-title":"Bleu: A Method for Automatic Evaluation of Machine Translation","volume-title":"Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics","author":"Papineni","year":"2002"},{"key":"ref44","volume-title":"Codet5: Identifier-aware unified pretrained encoder-decoder models for code understanding and generation","author":"Wang","year":"2021"},{"key":"ref45","volume-title":"Program Synthesis with Large Language Models","author":"Austin"},{"key":"ref46","article-title":"OMPGPT: A generative pretrained transformer model for openmp","author":"Chen","year":"2024","journal-title":"arXiv preprint"},{"key":"ref47","article-title":"MPIrigen: MPI Code Generation through Domain-Specific Language Models","author":"Schneider","year":"2024","journal-title":"arXiv preprint"},{"key":"ref48","author":"Grossman","year":"2023","journal-title":"ComPile: A Large IR Dataset from Production Sources"},{"key":"ref49","article-title":"Graphcodebert: Pretraining code representations with data flow","author":"Guo","year":"2020","journal-title":"arXiv preprint"},{"key":"ref50","article-title":"Code translation with compiler representations","author":"Szafraniec","year":"2022","journal-title":"arXiv preprint"},{"key":"ref51","article-title":"Compcodevet: A compiler-guided validation and enhancement approach for code dataset","author":"Chen","year":"2023","journal-title":"arXiv preprint"}],"event":{"name":"2024 IEEE High Performance Extreme Computing Conference (HPEC)","location":"Wakefield, MA, USA","start":{"date-parts":[[2024,9,23]]},"end":{"date-parts":[[2024,9,27]]}},"container-title":["2024 IEEE High Performance Extreme Computing Conference (HPEC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10938401\/10938415\/10938441.pdf?arnumber=10938441","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T15:47:41Z","timestamp":1743781661000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10938441\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,23]]},"references-count":51,"URL":"https:\/\/doi.org\/10.1109\/hpec62836.2024.10938441","relation":{},"subject":[],"published":{"date-parts":[[2024,9,23]]}}}