Deliverables Documents, reports (5) Report on porting applications and application tools to Sage2 system This deliverable reports the first experiences of porting use casestools to the Sage2 system It also reports on potential optimizations by leveraging Sage2 feature sets Sage2 ecosystem Design Document This report (from multiple tasks) will describe the design for all the Sage2 ecosystem components. This will get its inputs from Tasks 3.1 to 3.4 Best practices in porting and optimizing applications and application tools for Sage2 system In this report we will document experience and best practices obtained while porting and optimising applications to and for the Sage2 system including performance assessments It aims to provide practical guidance for future users of the technologies produced within this project Report on application and use case requirements This deliverable provides an analysis of IO requirements of Sage2 use cases and tools together with a data retention plan for each workflow This deliverable also identifies changes in applications and tools for fully using the Sage2 system and also limitations that might provide obstacles to their implementation System extrapolations to Exascale This deliverable will discuss the system extrapolations of the features and benefits of Sage2 for the use cases at scale and quantify the performance improvements in IO time to solution and scalability if there were larger scale deployments representative of the Sage2 prototype Analysis of how the system might actually perform in relation to the originally anticipated performance goals will be provided This deliverable will gather inputs from the use cases in WP1 Publications Conference proceedings (13) StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs Author(s): Artur Podobas, Martin Svedin, Steven W. D. Chien, Ivy B. Peng, Naresh Balaji Ravichandran, Pawel Herman, Anders Lansner, and Stefano Markidis Published in: 2021 Publisher: ACM DOI: 10.1145/3468044.3468052 Learning representations in Bayesian Confidence Propagation neural networks Author(s): Ravichandran, Naresh & Lansner, Anders & Herman, Pawel Published in: Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies (HEART '21). Association for Computing Machinery, New York, NY, USA, Article 8, 1–6, 2020 Publisher: IEEE DOI: 10.1109/ijcnn48605.2020.9207061 HPC systems in the next decade - what to expect, when, where Author(s): Pleiter, Dirk Published in: 24th International Conference on Computing in High Energy and Nuclear Physics, CHEP 2019, Adelaide, Australia, 2019-11-04 - 2019-11-08, Issue 1, 2019 Publisher: CHEP DOI: 10.5281/zenodo.3599755 Characterizing Deep-Learning I/O Workloads in TensorFlow Author(s): Steven W. D. Chien, Stefano Markidis, Chaitanya Prasad Sishtla, Luis Santos, Pawel Herman, Sai Narasimhamurthy, Erwin Laure Published in: 2018 IEEE/ACM 3rd International Workshop on Parallel Data Storage & Data Intensive Scalable Computing Systems (PDSW-DISCS), 2018, Page(s) 54-63, ISBN 978-1-7281-0192-7 Publisher: IEEE DOI: 10.1109/PDSW-DISCS.2018.00011 Sage2 - Percipient StorAGe for Exascale Data Centric Computing Author(s): Witt, Shaun de; Samaddar, Debby; Narasimhamurthy, Sai; Umanesan, Ganesan; Pleiter, Dirk; El Sayed Mohamed, Salem; Davis, Andrew Published in: 24th International Conference on Computing in High Energy and Nuclear Physics, CHEP 2019, Adelaide, Australia, 2019-11-04 - 2019-11-08, Issue 1, 2019 Publisher: CHEP Persistent coarrays - integrating MPI storage windows in coarray fortran Author(s): Sergio Rivas-Gomez, Alessandro Fanfarillo, Sai Narasimhamurthy, Stefano Markidis Published in: Proceedings of the 26th European MPI Users' Group Meeting on - EuroMPI '19, 2019, Page(s) 1-8, ISBN 9781-450371759 Publisher: ACM Press DOI: 10.1145/3343211.3343214 uMMAP-IO: User-Level Memory-Mapped I/O for HPC Author(s): Sergio Rivas-Gomez, Alessandro Fanfarillo, Sebastien Valat, Christophe Laferriere, Philippe Couvee, Sai Narasimhamurthy, Stefano Markidis Published in: 2019 IEEE 26th International Conference on High Performance Computing, Data, and Analytics (HiPC), 2019, Page(s) 363-372, ISBN 978-1-7281-4535-8 Publisher: IEEE DOI: 10.1109/hipc.2019.00051 Software Wear Management for Persistent Memories Author(s): Vaibhav Gogte, University of Michigan; William Wang and Stephan Diestelhorst, ARM; Aasheesh Kolli, Pennsylvania State University and VMware Research; Peter M. Chen, Satish Narayanasamy, and Thomas F. Wenisch, University of Michigan Published in: 17th USENIX Conference on File and Storage Technologies (FAST 19), 2019 Publisher: USENIX Association Brief Announcement - Persistent Atomics for Implementing Durable Lock-Free Data Structures for Non-Volatile Memory Author(s): William Wang, Stephan Diestelhorst Published in: The 31st ACM on Symposium on Parallelism in Algorithms and Architectures - SPAA '19, 2019, Page(s) 309-311, ISBN 9781-450361842 Publisher: ACM Press DOI: 10.1145/3323165.3323166 Relaxed Persist Ordering Using Strand Persistency Author(s): Vaibhav Gogte, William Wang, Stephan Diestelhorst, Peter M. Chen, Satish Narayanasamy, Thomas F. Wenisch Published in: ISCA '20: Proceedings of the 47th International Symposium on Computer Architecture, 2020 Publisher: Association for Computing Machinery Predicting File Lifetimes with Machine Learning Author(s): Thomas Leibovici, Florent Monjalet Published in: ISC High Performance 2019 International Workshops, 2019 Publisher: Springer In situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst Author(s): Atzori, M., Köpp, W., Chien, S.W.D. et al Published in: The Journal of Supercomputing, 2021 Publisher: Springer DOI: 10.1007/s11227-021-03990-3 NoaSci: A Numerical Object Array Library for I/O of Scientific Applications on Object Storage Author(s): Wei Der Chien, Artur Podobas, Martin Svedin, Andriy Tkachuk, Salem El Sayed, Pawel Herman, Ganesan Umanesan, Sai Narasimhamur thy and Stefano Markidis Published in: PDP 2022: International Conference on Parallel, Distributed and Network- Based Processing, 2022 Publisher: IEEE Peer reviewed articles (1) Language Support for Memory Persistency Author(s): Aasheesh Kolli, Vaibhav Gogte, Ali Saidi, Stephan Diestelhorst, William Wang, Peter M. Chen, Satish Narayanasamy, Thomas F. Wenisch Published in: IEEE Micro, Issue 39/3, 2019, Page(s) 94-102, ISSN 0272-1732 Publisher: Institute of Electrical and Electronics Engineers DOI: 10.1109/mm.2019.2910821 Other (1) tf-Darshan: UnderstandingFine-grainedI/O Performance in MachineLearning Workloads Author(s): Chien, Steven & Podobas, Artur & Peng, Ivy & Markidis, Stefano Published in: 2020 Publisher: IEEE DOI: 10.1109/cluster49012.2020.00046 Searching for OpenAIRE data... There was an error trying to search data from OpenAIRE No results available
