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ORCIDSaeed Maleki
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2020 – today
- 2024
[j4]Zhiqi Lin
, Youshan Miao, Guanbin Xu, Cheng Li, Olli Saarikivi, Saeed Maleki, Fan Yang:
Efficient Schedule Construction for Distributed Execution of Large DNN Models. IEEE Trans. Parallel Distributed Syst. 35(12): 2375-2391 (2024)- [c21]Abhinav Jangda, Saeed Maleki, Maryam Mehri Dehnavi, Madan Musuvathi, Olli Saarikivi:
A Framework for Fine-Grained Synchronization of Dependent GPU Kernels. CGO 2024: 93-105 - [c20]Guodong Liu, Youshan Miao, Zhiqi Lin, Xiaoxiang Shi, Saeed Maleki, Fan Yang, Yungang Bao, Sa Wang:
Aceso: Efficient Parallel DNN Training through Iterative Bottleneck Alleviation. EuroSys 2024: 163-181 - [c19]Zhiqi Lin, Youshan Miao, Guanbin Xu, Cheng Li, Olli Saarikivi, Saeed Maleki, Fan Yang:
Tessel: Boosting Distributed Execution of Large DNN Models via Flexible Schedule Search. HPCA 2024: 803-816 - [c18]Pratyush Patel, Esha Choukse, Chaojie Zhang, Aashaka Shah, Íñigo Goiri, Saeed Maleki, Ricardo Bianchini:
Splitwise: Efficient Generative LLM Inference Using Phase Splitting. ISCA 2024: 118-132 - [c17]Zhiqi Lin, Youshan Miao, Quanlu Zhang, Fan Yang, Yi Zhu, Cheng Li, Saeed Maleki, Xu Cao, Ning Shang, Yilei Yang, Weijiang Xu, Mao Yang, Lintao Zhang, Lidong Zhou:
nnScaler: Constraint-Guided Parallelization Plan Generation for Deep Learning Training. OSDI 2024: 347-363 - [i18]Liangyu Zhao, Saeed Maleki, Ziyue Yang, Hossein Pourreza, Aashaka Shah, Changho Hwang, Arvind Krishnamurthy:
ForestColl: Efficient Collective Communications on Heterogeneous Network Fabrics. CoRR abs/2402.06787 (2024) - 2023
- [c16]Meghan Cowan, Saeed Maleki, Madanlal Musuvathi, Olli Saarikivi, Yifan Xiong:
MSCCLang: Microsoft Collective Communication Language. ASPLOS (2) 2023: 502-514 - [c15]Aashaka Shah, Vijay Chidambaram, Meghan Cowan, Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, Jacob Nelson, Olli Saarikivi:
TACCL: Guiding Collective Algorithm Synthesis using Communication Sketches. NSDI 2023: 593-612 - [i17]Zhiqi Lin, Youshan Miao, Guodong Liu, Xiaoxiang Shi, Quanlu Zhang, Fan Yang, Saeed Maleki, Yi Zhu, Xu Cao, Cheng Li, Mao Yang, Lintao Zhang, Lidong Zhou:
SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction. CoRR abs/2301.08984 (2023) - [i16]Abhinav Jangda, Saeed Maleki, Maryam Mehri Dehnavi, Madan Musuvathi, Olli Saarikivi:
A Framework for Fine-Grained Synchronization of Dependent GPU Kernels. CoRR abs/2305.13450 (2023) - [i15]Behnaz Arzani, Siva Kesava Reddy Kakarla, Miguel Castro, Srikanth Kandula, Saeed Maleki, Luke Marshall:
Rethinking Machine Learning Collective Communication as a Multi-Commodity Flow Problem. CoRR abs/2305.13479 (2023) - [i14]Saeed Maleki:
Look-Up mAI GeMM: Increasing AI GeMMs Performance by Nearly 2.5x via msGeMM. CoRR abs/2310.06178 (2023) - [i13]Zhiqi Lin, Youshan Miao, Guanbin Xu, Cheng Li, Olli Saarikivi, Saeed Maleki, Fan Yang:
Tessel: Boosting Distributed Execution of Large DNN Models via Flexible Schedule Search. CoRR abs/2311.15269 (2023) - [i12]Pratyush Patel, Esha Choukse, Chaojie Zhang, Íñigo Goiri, Aashaka Shah, Saeed Maleki, Ricardo Bianchini:
Splitwise: Efficient generative LLM inference using phase splitting. CoRR abs/2311.18677 (2023) - 2022
- [c14]Abhinav Jangda, Jun Huang, Guodong Liu, Amir Hossein Nodehi Sabet, Saeed Maleki, Youshan Miao, Madanlal Musuvathi, Todd Mytkowicz, Olli Saarikivi:
Breaking the computation and communication abstraction barrier in distributed machine learning workloads. ASPLOS 2022: 402-416 - [i11]Meghan Cowan, Saeed Maleki, Madanlal Musuvathi, Olli Saarikivi, Yifan Xiong:
MSCCL: Microsoft Collective Communication Library. CoRR abs/2201.11840 (2022) - [i10]Saeed Maleki, Adhiti Raman, Yang Cheng, John L. Crassidis, Matthias Schmid:
Optimal Pose Estimation and Covariance Analysis with Simultaneous Localization and Mapping Applications. CoRR abs/2210.11697 (2022) - [i9]Saeed Maleki, John L. Crassidis, Yang Cheng, Matthias Schmid:
Error-Covariance Analysis of Monocular Pose Estimation Using Total Least Squares. CoRR abs/2210.12157 (2022) - 2021
- [c13]Gurbinder Gill, Roshan Dathathri, Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, Olli Saarikivi:
Distributed Training of Embeddings using Graph Analytics. IPDPS 2021: 973-983 - [c12]Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, Olli Saarikivi, Tianju Xu, Vadim Eksarevskiy, Jaliya Ekanayake, Emad Barsoum:
Scaling Distributed Training with Adaptive Summation. MLSys 2021 - [c11]Zixian Cai, Zhengyang Liu, Saeed Maleki, Madanlal Musuvathi, Todd Mytkowicz, Jacob Nelson, Olli Saarikivi:
Synthesizing optimal collective algorithms. PPoPP 2021: 62-75 - [i8]Abhinav Jangda, Jun Huang, Guodong Liu, Amir Hossein Nodehi Sabet, Saeed Maleki, Youshan Miao, Madanlal Musuvathi, Todd Mytkowicz, Olli Saarikivi:
CoCoNet: Co-Optimizing Computation and Communication for Distributed Machine Learning. CoRR abs/2105.05720 (2021) - [i7]Saeed Maleki, John L. Crassidis, Yang Cheng, Matthias Schmid:
Total Least Squares for Optimal Pose Estimation. CoRR abs/2106.11522 (2021) - [i6]Aashaka Shah, Vijay Chidambaram, Meghan Cowan, Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, Jacob Nelson, Olli Saarikivi, Rachee Singh:
Synthesizing Collective Communication Algorithms for Heterogeneous Networks with TACCL. CoRR abs/2111.04867 (2021) - 2020
- [i5]Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, Olli Saarikivi, Tianju Xu, Vadim Eksarevskiy, Jaliya Ekanayake, Emad Barsoum:
Scaling Distributed Training with Adaptive Summation. CoRR abs/2006.02924 (2020) - [i4]Zixian Cai, Zhengyang Liu, Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, Jacob Nelson, Olli Saarikivi:
Synthesizing Optimal Collective Algorithms. CoRR abs/2008.08708 (2020)
2010 – 2019
- 2019
- [c10]Roshan Dathathri, Olli Saarikivi, Hao Chen, Kim Laine, Kristin E. Lauter, Saeed Maleki, Madanlal Musuvathi, Todd Mytkowicz:
CHET: an optimizing compiler for fully-homomorphic neural-network inferencing. PLDI 2019: 142-156 - [i3]Gurbinder Gill, Roshan Dathathri, Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, Olli Saarikivi:
Distributed Word2Vec using Graph Analytics Frameworks. CoRR abs/1909.03359 (2019) - 2018
- [j3]Zhangxiaowen Gong, Zhi Chen, Justin Josef Szaday, David C. Wong, Zehra Sura, Neftali Watkinson, Saeed Maleki, David A. Padua, Alexander V. Veidenbaum, Alexandru Nicolau, Josep Torrellas:
An empirical study of the effect of source-level loop transformations on compiler stability. Proc. ACM Program. Lang. 2(OOPSLA): 126:1-126:29 (2018) - [c9]Saeed Maleki, Madanlal Musuvathi, Todd Mytkowicz:
Semantics-Preserving Parallelization of Stochastic Gradient Descent. IPDPS 2018: 224-233 - [i2]Roshan Dathathri, Olli Saarikivi, Hao Chen, Kim Laine, Kristin E. Lauter, Saeed Maleki, Madanlal Musuvathi, Todd Mytkowicz:
CHET: Compiler and Runtime for Homomorphic Evaluation of Tensor Programs. CoRR abs/1810.00845 (2018) - 2017
- [c8]Zhi Chen, Zhangxiaowen Gong, Justin Josef Szaday, David C. Wong, David A. Padua, Alexandru Nicolau, Alexander V. Veidenbaum, Neftali Watkinson, Zehra Sura, Saeed Maleki, Josep Torrellas, Gerald DeJong:
LORE: A loop repository for the evaluation of compilers. IISWC 2017: 219-228 - [i1]Saeed Maleki, Madanlal Musuvathi, Todd Mytkowicz:
Parallel Stochastic Gradient Descent with Sound Combiners. CoRR abs/1705.08030 (2017) - 2016
- [j2]Saeed Maleki, Madanlal Musuvathi, Todd Mytkowicz:
Efficient parallelization using rank convergence in dynamic programming algorithms. Commun. ACM 59(10): 85-92 (2016) - [j1]Saeed Maleki, Madanlal Musuvathi, Todd Mytkowicz:
Low-Rank Methods for Parallelizing Dynamic Programming Algorithms. ACM Trans. Parallel Comput. 2(4): 26:1-26:32 (2016) - [c7]Charith Mendis, Jasha Droppo, Saeed Maleki, Madanlal Musuvathi, Todd Mytkowicz, Geoffrey Zweig:
Parallelizing WFST speech decoders. ICASSP 2016: 5325-5329 - [c6]Saeed Maleki, Donald Nguyen, Andrew Lenharth, María Jesús Garzarán, David A. Padua, Keshav Pingali:
DSMR: A Parallel Algorithm for Single-Source Shortest Path Problem. ICS 2016: 32:1-32:14 - [c5]Saeed Maleki, Donald Nguyen, Andrew Lenharth, María Jesús Garzarán, David A. Padua, Keshav Pingali:
DSMR: a shared and distributed memory algorithm for single-source shortest path problem. PPoPP 2016: 39:1-39:2 - 2015
- [b1]Saeed Maleki:
Communication avoiding parallel algorithms for amorphous problems. University of Illinois Urbana-Champaign, USA, 2015 - 2014
- [c4]Saeed Maleki, G. Carl Evans, David A. Padua:
Tiled Linear Algebra a System for Parallel Graph Algorithms. LCPC 2014: 116-130 - [c3]Saeed Maleki, Madanlal Musuvathi, Todd Mytkowicz:
Parallelizing dynamic programming through rank convergence. PPoPP 2014: 219-232 - 2012
- [c2]Albert Sidelnik, Saeed Maleki, Bradford L. Chamberlain, María Jesús Garzarán, David A. Padua:
Performance Portability with the Chapel Language. IPDPS 2012: 582-594 - 2011
- [c1]Saeed Maleki, Yaoqing Gao, María Jesús Garzarán, Tommy Wong, David A. Padua:
An Evaluation of Vectorizing Compilers. PACT 2011: 372-382
Coauthor Index
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