MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems.
Steven FarrellMurali EmaniJacob BalmaLukas DrescherAleksandr DrozdAndreas FinkGeoffrey C. FoxDavid KanterThorsten KurthPeter MattsonDawei MuAmit RuhelaKento SatoKoichi ShirahataTsuguchika TabaruAristeidis TsarisJan BalewskiBen CummingTakumi DanjoJens DomkeTakaaki FukaiNaoto FukumotoTatsuya FukushiBalazs GerofiTakumi HondaToshiyuki ImamuraAkihiko KasagiKentaro KawakamiShuhei KudoAkiyoshi KurodaMaxime MartinassoSatoshi MatsuokaHenrique MendonçaKazuki MinamiPrabhat RamTakashi SawadaMallikarjun ShankarTom St. JohnAkihiro TabuchiVenkatram VishwanathMohamed WahibMasafumi YamazakiJunqi YinPublished in: MLHPC@SC (2021)
Keyphrases
- machine learning
- high performance computing
- benchmark suite
- scientific computing
- computational science
- fault tolerance
- data mining
- computing systems
- computer systems
- information retrieval
- computer vision
- machine learning approaches
- distributed systems
- intelligent systems
- computational intelligence
- complex systems
- learning systems
- real time
- expert systems
- pattern recognition
- text mining
- power consumption
- information extraction
- knowledge representation
- active learning
- genetic algorithm
- databases