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Mohammad Mahdi Javanmard
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2020 – today
- 2024
- [j1]Martin Maas, David G. Andersen, Michael Isard, Mohammad Mahdi Javanmard, Kathryn S. McKinley, Colin Raffel:
Combining Machine Learning and Lifetime-Based Resource Management for Memory Allocation and Beyond. Commun. ACM 67(4): 87-96 (2024) - 2022
- [c11]Joseph Schuchart
, Poornima Nookala
, Mohammad Mahdi Javanmard, Thomas Hérault
, Edward F. Valeev
, George Bosilca, Robert J. Harrison:
Generalized Flow-Graph Programming Using Template Task-Graphs: Initial Implementation and Assessment. IPDPS 2022: 839-849 - [c10]Zafar Ahmad, Mohammad Mahdi Javanmard, Gregory Thomas Croisdale
, Aaron Gregory, Pramod Ganapathi, Louis-Noël Pouchet, Rezaul Chowdhury:
FOURST: A code generator for FFT-based fast stencil computations. ISPASS 2022: 99-108 - 2021
- [c9]Poornima Nookala
, Zafar Ahmad
, Mohammad Mahdi Javanmard, Martin Kong
, Rezaul Chowdhury, Robert J. Harrison:
Understanding Recursive Divide-and-Conquer Dynamic Programs in Fork-Join and Data-Flow Execution Models. IPDPS Workshops 2021: 407-416 - [c8]Zafar Ahmad
, Rezaul Chowdhury, Rathish Das, Pramod Ganapathi, Aaron Gregory, Mohammad Mahdi Javanmard:
Low-Span Parallel Algorithms for the Binary-Forking Model. SPAA 2021: 22-34 - 2020
- [c7]Martin Maas, David G. Andersen, Michael Isard, Mohammad Mahdi Javanmard, Kathryn S. McKinley, Colin Raffel:
Learning-based Memory Allocation for C++ Server Workloads. ASPLOS 2020: 541-556 - [c6]Mohammad Mahdi Javanmard, Zafar Ahmad
, Martin Kong
, Louis-Noël Pouchet, Rezaul Chowdhury, Robert J. Harrison:
Deriving parametric multi-way recursive divide-and-conquer dynamic programming algorithms using polyhedral compilers. CGO 2020: 317-329 - [c5]Mohammad Mahdi Javanmard, Zafar Ahmad
, Jaroslaw Zola, Louis-Noël Pouchet, Rezaul Chowdhury, Robert J. Harrison:
Efficient Execution of Dynamic Programming Algorithms on Apache Spark. CLUSTER 2020: 337-348 - [c4]George Bosilca, Robert J. Harrison, Thomas Hérault
, Mohammad Mahdi Javanmard, Poornima Nookala
, Edward F. Valeev
:
The Template Task Graph (TTG) - an emerging practical dataflow programming paradigm for scientific simulation at extreme scale. ESPM2@SC 2020: 1-7 - [i1]Zafar Ahmad, Rezaul Chowdhury, Rathish Das, Pramod Ganapathi, Aaron Gregory, Mohammad Mahdi Javanmard:
Low-Depth Parallel Algorithms for the Binary-Forking Model without Atomics. CoRR abs/2008.13292 (2020)
2010 – 2019
- 2019
- [c3]Mohammad Mahdi Javanmard, Pramod Ganapathi, Rathish Das, Zafar Ahmad, Stephen L. Tschudi, Rezaul Chowdhury:
Toward efficient architecture-independent algorithms for dynamic programs: poster. PPoPP 2019: 413-414 - [c2]Mohammad Mahdi Javanmard, Pramod Ganapathi, Rathish Das, Zafar Ahmad
, Stephen L. Tschudi, Rezaul Chowdhury:
Toward Efficient Architecture-Independent Algorithms for Dynamic Programs. ISC 2019: 143-164 - 2011
- [c1]Hassan Haghighi, Mohammad Mahdi Javanmard:
Constructive Development of Probabilistic Programs. FSEN 2011: 80-95
Coauthor Index
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last updated on 2024-08-05 21:16 CEST by the dblp team
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