Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Chris J. Newburn"'
Autor:
Gilad Shainer, Richard Graham, Chris J. Newburn, Oscar Hernandez, Gil Bloch, Tom Gibbs, Jack C. Wells
Publikováno v:
Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation ISBN: 9783030964979
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5baf49bdfbbfb2357be2c5342707b68f
https://doi.org/10.1007/978-3-030-96498-6_20
https://doi.org/10.1007/978-3-030-96498-6_20
Publikováno v:
P3HPC@SC
Great strides have been made to enable performance, portability, and productivity in HPC, but the focus has so far been on standalone applications and on-node programming models. Complex workflows comprising many communicating orchestrators, services
Publikováno v:
IPDPS Workshops
High Performance Computing has been a driving force behind important tasks such as scientific discovery and deep learning. It tends to achieve performance through greater concurrency and heterogeneity, where the underlying complexity of richer topolo
Autor:
Chris J. Newburn, Neena Imam, Sreeram Potluri, Anshuman Goswami, Manjunath Gorentla Venkata, Ching-Hsiang Chu
Publikováno v:
OpenSHMEM and Related Technologies. OpenSHMEM in the Era of Extreme Heterogeneity ISBN: 9783030049171
OpenSHMEM
OpenSHMEM
Graphics Processing Units (GPUs) are popular for their massive parallelism and high bandwidth memory and are being increasingly used in data-intensive applications. In this context, GPU-based In-Memory Key-Value (G-IMKV) Stores have been proposed to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef65c246d4d6b0b31fddf47eab59288f
https://doi.org/10.1007/978-3-030-04918-8_10
https://doi.org/10.1007/978-3-030-04918-8_10
Autor:
John Shalf, Anshu Dubey, Jeff Keasler, Miquel Pericas, Bradford L. Chamberlain, H. Carter Edwards, Romain E. Cledat, Hal Finkel, Emmanuel Jeannot, Vitus J. Leung, Amir Kamil, Hatem Ltaief, Paul H. J. Kelly, Didem Unat, Mark Abraham, Mauro Bianco, Naoya Maruyama, Frank Hannig, Karl Fuerlinger, Chris J. Newburn, Torsten Hoefler
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems, vol 28, iss 10
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems, 2017, 28 (10), pp.3007-3020. ⟨10.1109/TPDS.2017.2703149⟩
Unat, D; Dubey, A; Hoefler, T; Shalf, JB; Abraham, M; Bianco, M; et al.(2017). Trends in Data Locality Abstractions for HPC Systems. IEEE Transactions on Parallel and Distributed Systems, 28(10), 3007-3020. doi: 10.1109/TPDS.2017.2703149. Lawrence Berkeley National Laboratory: Retrieved from: http://www.escholarship.org/uc/item/8v30n4hf
IEEE Transactions on Parallel and Distributed Systems, Institute of Electrical and Electronics Engineers, 2017, 28 (10), pp.3007-3020. ⟨10.1109/TPDS.2017.2703149⟩
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems, 2017, 28 (10), pp.3007-3020. ⟨10.1109/TPDS.2017.2703149⟩
Unat, D; Dubey, A; Hoefler, T; Shalf, JB; Abraham, M; Bianco, M; et al.(2017). Trends in Data Locality Abstractions for HPC Systems. IEEE Transactions on Parallel and Distributed Systems, 28(10), 3007-3020. doi: 10.1109/TPDS.2017.2703149. Lawrence Berkeley National Laboratory: Retrieved from: http://www.escholarship.org/uc/item/8v30n4hf
IEEE Transactions on Parallel and Distributed Systems, Institute of Electrical and Electronics Engineers, 2017, 28 (10), pp.3007-3020. ⟨10.1109/TPDS.2017.2703149⟩
International audience; The cost of data movement has always been an important concern in high performance computing (HPC) systems. It has now become the dominant factor in terms of both energy consumption and performance. Support for expression of d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fad3f59cfa8f6f0aa75364c19811e73a
https://escholarship.org/uc/item/8v30n4hf
https://escholarship.org/uc/item/8v30n4hf
Autor:
Chris J. Newburn, Gaurav Bansal, Michael Wood, Luis Crivelli, Judit Planas, Alejandro Duran, Paulo Souza, Leonardo Borges, Piotr Luszczek, Stanimire Tomov, Jack Dongarra, Hartwig Anzt, Mark Gates, Azzam Haidar, Yulu Jia, Khairul Kabir, Ichitaro Yamazaki, Jesus Labarta
Publikováno v:
2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW).
Autor:
Brooke Fugate, Shiliang Hu, Chris J. Newburn, Akshitha Sriraman, Joseph Devietti, Gilles Pokam, Liang Luo
Publikováno v:
HPCA
Contention for shared memory, in the forms of true sharing and false sharing, is a challenging performance bug to discover and to repair. Understanding cache contention requires global knowledge of the program's actual sharing behavior, and can even
Autor:
Michael Klemm, Matthias Noack, Georg Zitzlsberger, Thomas Steinke, Chris J. Newburn, Florian Wende
Publikováno v:
Euro-Par 2016: Parallel Processing ISBN: 9783319436586
Euro-Par
Euro-Par
Effective vectorization is becoming increasingly important for high performance and energy efficiency on processors with wide SIMD units. Compilers often require programmers to identify opportunities for vectorization, using directives to disprove da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8d500c2ec5c43beda7f6055d0f48d3a
https://doi.org/10.1007/978-3-319-43659-3_20
https://doi.org/10.1007/978-3-319-43659-3_20
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319460789
ISC Workshops
ISC Workshops
Many-core hardware platforms offer a tremendous opportunity for scaling up performance, but not all codes that run on these platforms have been modernized sufficiently to fully utilize the hardware. Assessing whether a code will effectively utilize a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a11e2d035c97c8e88781ed54519a6453
https://doi.org/10.1007/978-3-319-46079-6_23
https://doi.org/10.1007/978-3-319-46079-6_23
Publikováno v:
Second EAGE Workshop on High Performance Computing for Upstream.
Today’s platforms are becoming increasingly heterogeneous. A given platform may have many different computing elements in it: CPUs, coprocessors and GPUs of various kinds. And over time, the platforms on which seismic codes run may change, such tha