{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T01:37:04Z","timestamp":1772933824398,"version":"3.50.1"},"reference-count":35,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T00:00:00Z","timestamp":1765152000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T00:00:00Z","timestamp":1765152000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,8]]},"DOI":"10.1109\/bigdata66926.2025.11400821","type":"proceedings-article","created":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T20:57:57Z","timestamp":1772830677000},"page":"2503-2512","source":"Crossref","is-referenced-by-count":0,"title":["Serverless GPU Architecture for Enterprise HR Analytics: A Production-Scale BDaaS Implementation"],"prefix":"10.1109","author":[{"given":"Guilin","family":"Zhang","sequence":"first","affiliation":[{"name":"George Washington University,Department of Engineering Management and Systems Engineering,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wulan","family":"Guo","sequence":"additional","affiliation":[{"name":"George Washington University,Department of Engineering Management and Systems Engineering,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziqi","family":"Tan","sequence":"additional","affiliation":[{"name":"George Washington University,Department of Engineering Management and Systems Engineering,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Srinivas","family":"Vippagunta","sequence":"additional","affiliation":[{"name":"Workday, Inc."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suchitra","family":"Raman","sequence":"additional","affiliation":[{"name":"Workday, Inc."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shreeshankar","family":"Chatterjee","sequence":"additional","affiliation":[{"name":"Workday, Inc."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ju","family":"Lin","sequence":"additional","affiliation":[{"name":"Workday, Inc."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shang","family":"Liu","sequence":"additional","affiliation":[{"name":"Workday, Inc."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mary","family":"Schladenhauffen","sequence":"additional","affiliation":[{"name":"Workday, Inc."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey","family":"Luo","sequence":"additional","affiliation":[{"name":"Workday, Inc."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hailong","family":"Jiang","sequence":"additional","affiliation":[{"name":"Youngstown State University,Department of Computer Science and Information Technology,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"issue":"10","key":"ref1","first-page":"52","article-title":"Competing on talent analytics","volume":"88","author":"Davenport","year":"2010","journal-title":"Harvard business review"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1080\/09585192.2016.1244699"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.48175\/ijarsct-13555c"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.17705\/1CAIS.01603"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s11846-022-00574-0"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3190664"},{"key":"ref7","author":"Fedorovych","year":"2024","journal-title":"Performance benchmarking of continuous processing and micro-batch modes in spark structured streaming"},{"key":"ref8","volume-title":"Data Frame Structures and Manipulation: Definitive Reference for Developers and Engineers","author":"Johnson","year":"2025"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/IPCCC66453.2025.11304654"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.30574\/wjarr.2025.26.2.1746"},{"issue":"4","key":"ref11","article-title":"Apache flink: Stream and batch processing in a single engine","volume":"38","author":"Carbone","year":"2015","journal-title":"The Bulletin of the Technical Committee on Data Engineering"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-023-00814-z"},{"key":"ref13","volume-title":"Cloud run gpus are now generally available. Google Cloud","year":"2025"},{"key":"ref14","volume-title":"Announcing ga for azure container apps serverless gpus. Microsoft Azure","year":"2025"},{"key":"ref15","author":"Zhao","year":"2024","journal-title":"Towards fast setup and high throughput of gpu serverless computing"},{"key":"ref16","author":"Yu","year":"2025","journal-title":"Torpor: Gpu-enabled serverless computing for low-latency, resource-efficient inference"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/FMEC65595.2025.11119384"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0215450"},{"key":"ref19","first-page":"1","article-title":"Security requirements for cryptographic modules","author":"Brown","year":"1994","journal-title":"Fed. Inf. Process. Stand. Publ"},{"key":"ref20","author":"Zhu","year":"2022","journal-title":"Dissecting service mesh overheads"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i8.16826"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3368454"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2020.01.004"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS54959.2023.00093"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3229161"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3321\/j.issn:0529-6579.2007.z1.029"},{"key":"ref27","first-page":"800","article-title":"Security and privacy controls for information systems and organizations","author":"Force","year":"2017","journal-title":"National Institute of Standards and Technology, NIST Special Publication"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.5259339"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3617574.3617859"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2020.2975749"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2018.00035"},{"key":"ref32","article-title":"Artificial intelligence risk management framework: Generative artificial intelligence profile","author":"AI","year":"2024","journal-title":"NIST Trustworthy and Responsible AI Gaithersburg, MD, USA"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01057-7_56"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.3390\/math11224677"},{"key":"ref35","article-title":"Equality of opportunity in supervised learning","volume":"29","author":"Hardt","year":"2016","journal-title":"Advances in neural information processing systems"}],"event":{"name":"2025 IEEE International Conference on Big Data (BigData)","location":"Macau, China","start":{"date-parts":[[2025,12,8]]},"end":{"date-parts":[[2025,12,11]]}},"container-title":["2025 IEEE International Conference on Big Data (BigData)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11400704\/11400712\/11400821.pdf?arnumber=11400821","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T06:52:47Z","timestamp":1772866367000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11400821\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,8]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/bigdata66926.2025.11400821","relation":{},"subject":[],"published":{"date-parts":[[2025,12,8]]}}}