Статті для всіх - Vivek SarkarДокладніше
Недоступно ніде: 11
SWAT: A programmable, in-memory, distributed, high-performance computing platform
M Grossman, V Sarkar
Proceedings of the 25th ACM International Symposium on High-Performance …, 2016
Мандати: US National Science Foundation
Pipes: a language and compiler for task-based programming on distributed-memory clusters
M Kong, LN Pouchet, P Sadayappan, V Sarkar
SC'16: Proceedings of the International Conference for High Performance …, 2016
Мандати: US National Science Foundation, US Department of Energy
High performance multilevel graph partitioning on GPU
B Goodarzi, F Khorasani, V Sarkar, D Goswami
2019 International Conference on High Performance Computing & Simulation …, 2019
Мандати: Natural Sciences and Engineering Research Council of Canada
Optimized two-level parallelization for gpu accelerators using the polyhedral model
J Shirako, A Hayashi, V Sarkar
Proceedings of the 26th international conference on compiler construction, 22-33, 2017
Мандати: US National Science Foundation
Design, verification and applications of a new read-write lock algorithm
J Shirako, N Vrvilo, EG Mercer, V Sarkar
Proceedings of the twenty-fourth annual ACM symposium on Parallelism in …, 2012
Мандати: US National Institutes of Health
Transitive joins: a sound and efficient online deadlock-avoidance policy
C Voss, T Cogumbreiro, V Sarkar
Proceedings of the 24th Symposium on Principles and Practice of Parallel …, 2019
Мандати: US National Science Foundation
Implementation and evaluation of OpenSHMEM contexts using OFI libfabric
M Grossman, J Doyle, J Dinan, H Pritchard, K Seager, V Sarkar
OpenSHMEM and Related Technologies. Big Compute and Big Data Convergence …, 2018
Мандати: US Department of Defense
Automatic parallelization of pure method calls via conditional future synthesis
R Surendran, V Sarkar
ACM SIGPLAN Notices 51 (10), 20-38, 2016
Мандати: US National Science Foundation
OpenMP as a High-Level Specification Language for Parallelism: And its use in Evaluating Parallel Programming Systems
M Grossman, J Shirako, V Sarkar
OpenMP: Memory, Devices, and Tasks: 12th International Workshop on OpenMP …, 2016
Мандати: US National Science Foundation
Highly scalable large-scale asynchronous graph processing using actors
Y Elmougy, A Hayashi, V Sarkar
2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet …, 2023
Мандати: US Department of Defense, US Office of the Director of National Intelligence
HOOVER: Leveraging OpenSHMEM for High Performance, Flexible Streaming Graph Applications
M Grossman, H Pritchard, S Poole, V Sarkar
2020 IEEE/ACM 3rd Annual Parallel Applications Workshop: Alternatives To …, 2020
Мандати: US Department of Energy, US Department of Defense
Доступно в інших місцях: 64
Understanding reuse, performance, and hardware cost of dnn dataflow: A data-centric approach
H Kwon, P Chatarasi, M Pellauer, A Parashar, V Sarkar, T Krishna
Proceedings of the 52nd Annual IEEE/ACM International Symposium on …, 2019
Мандати: US National Science Foundation
Maestro: A data-centric approach to understand reuse, performance, and hardware cost of dnn mappings
H Kwon, P Chatarasi, V Sarkar, T Krishna, M Pellauer, A Parashar
IEEE micro 40 (3), 20-29, 2020
Мандати: US National Science Foundation
The Open Community Runtime: A runtime system for extreme scale computing
TG Mattson, R Cledat, V Cavé, V Sarkar, Z Budimlić, S Chatterjee, ...
2016 IEEE High Performance Extreme Computing Conference (HPEC), 1-7, 2016
Мандати: US Department of Energy
T2s-tensor: Productively generating high-performance spatial hardware for dense tensor computations
N Srivastava, H Rong, P Barua, G Feng, H Cao, Z Zhang, D Albonesi, ...
2019 IEEE 27th Annual International Symposium on Field-Programmable Custom …, 2019
Мандати: US National Science Foundation, US Department of Defense, National Natural …
Habaneroupc++ a coMPIler-free pgas library
V Kumar, Y Zheng, V Cavé, Z Budimlić, V Sarkar
Proceedings of the 8th International Conference on Partitioned Global …, 2014
Мандати: US Department of Energy
Marvel: A data-centric approach for mapping deep learning operators on spatial accelerators
P Chatarasi, H Kwon, A Parashar, M Pellauer, T Krishna, V Sarkar
ACM Transactions on Architecture and Code Optimization (TACO) 19 (1), 1-26, 2021
Мандати: US National Science Foundation, US Department of Energy
Regmutex: Inter-warp gpu register time-sharing
F Khorasani, HA Esfeden, A Farmahini-Farahani, N Jayasena, V Sarkar
2018 ACM/IEEE 45th Annual International Symposium on Computer Architecture …, 2018
Мандати: US National Science Foundation
Modeling the conflicting demands of parallelism and temporal/spatial locality in affine scheduling
O Zinenko, S Verdoolaege, C Reddy, J Shirako, T Grosser, V Sarkar, ...
Proceedings of the 27th International Conference on Compiler Construction, 3-13, 2018
Мандати: US Department of Energy
OpenMP application experiences: Porting to accelerated nodes
S Bak, C Bertoni, S Boehm, R Budiardja, BM Chapman, J Doerfert, ...
Parallel Computing 109, 102856, 2022
Мандати: US National Science Foundation, US Department of Energy
Дані про публікацію й грошову підтримку визначаються автоматично комп'ютерною програмою