Zobrazeno 1 - 10
of 29
pro vyhledávání: '"John D. Leidel"'
Publikováno v:
IEEE Transactions on Computers. 70:833-848
Emerging High-Performance Computing (HPC) workloads, such as graph analytics, machine learning, and big data science, are data-intensive. Data-intensive workloads usually present fine-grained memory accesses with limited or no data locality, and thus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7e2c99480a6cec000c420bb56239d36
https://doi.org/10.1109/tc.2021.3066982
https://doi.org/10.1109/tc.2021.3066982
Publikováno v:
ACM Transactions on Parallel Computing. 7:1-24
Given the increasing importance of efficient data-intensive computing, we find that modern processor designs are not well suited to the irregular memory access patterns often found in these algorithms. Applications and algorithms that do not exhibit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e3e5972a1b2ba18efd9c2012326427c
https://doi.org/10.1145/3418082
https://doi.org/10.1145/3418082
Publikováno v:
OpenSHMEM and Related Technologies. OpenSHMEM in the Era of Exascale and Smart Networks ISBN: 9783031048876
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e0031ef5845260d6642b2b6b700bb384
https://doi.org/10.1007/978-3-031-04888-3_6
https://doi.org/10.1007/978-3-031-04888-3_6
Publikováno v:
2021 IEEE High Performance Extreme Computing Conference (HPEC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07aff5597ffa55860c06b82ace7f2734
https://doi.org/10.1109/hpec49654.2021.9622817
https://doi.org/10.1109/hpec49654.2021.9622817
Publikováno v:
IPDPS
The tremendous expansion of data volume has driven the transition from monolithic architectures towards systems integrated with discrete and distributed subcomponents in modern scalable high performance computing (HPC) systems. As such, multi-layered
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::947db5cf4fcb71d1e03838727daacc71
https://doi.org/10.1109/ipdps49936.2021.00054
https://doi.org/10.1109/ipdps49936.2021.00054
Publikováno v:
DAC
Emerging data-intensive applications such as graph analytics, machine learning, and data-driven scientific computing are driving the evolution of high-performance computing (HPC) systems from monolithic to scaled-out, heterogeneous, and complex archi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::770edbc88d11f27185d9d1d68adf988d
https://doi.org/10.1109/dac18072.2020.9218589
https://doi.org/10.1109/dac18072.2020.9218589
Publikováno v:
HPDC
Many contemporary data-intensive applications exhibit irregular and highly concurrent memory access patterns and thus challenge the performance of conventional memory systems. Driven by an expanding need for high-bandwidth memory featuring low access
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::526bad919237657c8afc7601643b3733
https://doi.org/10.1145/3369583.3392670
https://doi.org/10.1145/3369583.3392670
Publikováno v:
CF
As the density and capability of reconfigurable computing using FPGAs continues to increase and access to large scale ASIC integration continues to increase, research activities associated with high level synthesis flows have expanded at a similar ra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50ef38d458b5ad3063d9c8030718849f
https://doi.org/10.1145/3387902.3394029
https://doi.org/10.1145/3387902.3394029
Autor:
John D. Leidel, Yong Chen
Publikováno v:
Parallel Computing. 68:77-88
The recent advent of stacked memory devices has led to a resurgence of research associated with the fundamental memory hierarchy and associated memory pipeline. The bandwidth advantages provided by stacked logic and DRAM devices have inspired researc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3524c80b3082de367d53ee7e011be268
https://doi.org/10.1016/j.parco.2017.07.008
https://doi.org/10.1016/j.parco.2017.07.008
Publikováno v:
PACT
Emerging High-Performance Computing (HPC) workloads, such as graph analytics, machine learning, big data science, are data-intensive. The data-intensive workloads usually present irregular memory footprints with limited data locality, and thus incur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b1be930948fa8a388d4ef217030326d
https://doi.org/10.1109/pact.2019.00048
https://doi.org/10.1109/pact.2019.00048