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ORCIDTao B. Schardl
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- affiliation (PhD 2016): Massachusetts Institute of Technology, Cambridge, USA
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Books and Theses
- 2016
[b1]Tao Benjamin Schardl:
Performance engineering of multicore software: developing a science of fast code for the post-Moore era. Massachusetts Institute of Technology, Cambridge, USA, 2016
Journal Articles
- 2019
- [j10]Tao B. Schardl, William S. Moses
, Charles E. Leiserson:
Tapir: Embedding Recursive Fork-join Parallelism into LLVM's Intermediate Representation. ACM Trans. Parallel Comput. 6(4): 19:1-19:33 (2019) - 2018
- [j9]I-Ting Angelina Lee, Tao B. Schardl:
Efficient Race Detection for Reducer Hyperobjects. ACM Trans. Parallel Comput. 4(4): 20:1-20:40 (2018) - 2017
- [j8]Tao B. Schardl, Tyler Denniston, Damon Doucet, Bradley C. Kuszmaul, I-Ting Angelina Lee, Charles E. Leiserson:
The CSI Framework for Compiler-Inserted Program Instrumentation. Proc. ACM Meas. Anal. Comput. Syst. 1(2): 43:1-43:25 (2017) - 2016
- [j7]Warut Suksompong, Charles E. Leiserson, Tao B. Schardl:
On the efficiency of localized work stealing. Inf. Process. Lett. 116(2): 100-106 (2016) - [j6]Charles E. Leiserson, Tao B. Schardl, Warut Suksompong:
Upper Bounds on Number of Steals in Rooted Trees. Theory Comput. Syst. 58(2): 223-240 (2016) - [j5]Tim Kaler, William Hasenplaugh, Tao B. Schardl, Charles E. Leiserson:
Executing Dynamic Data-Graph Computations Deterministically Using Chromatic Scheduling. ACM Trans. Parallel Comput. 3(1): 2:1-2:31 (2016) - 2015
- [j4]I-Ting Angelina Lee, Charles E. Leiserson, Tao B. Schardl, Zhunping Zhang, Jim Sukha:
On-the-Fly Pipeline Parallelism. ACM Trans. Parallel Comput. 2(3): 17:1-17:42 (2015) - 2013
- [j3]Zachary Abel, Erik D. Demaine, Martin L. Demaine, Sarah Eisenstat, Jayson Lynch, Tao B. Schardl, Isaac Shapiro-Ellowitz:
Folding Equilateral Plane graphs. Int. J. Comput. Geom. Appl. 23(2): 75-92 (2013) - [j2]Zachary Abel, Erik D. Demaine, Martin L. Demaine, Sarah Eisenstat, Jayson Lynch, Tao B. Schardl:
Finding a Hamiltonian Path in a Cube with Specified Turns is Hard. Inf. Media Technol. 8(3): 685-694 (2013) - [j1]Zachary Abel, Erik D. Demaine, Martin L. Demaine, Sarah Eisenstat, Jayson Lynch, Tao B. Schardl:
Finding a Hamiltonian Path in a Cube with Specified Turns is Hard. J. Inf. Process. 21(3): 368-377 (2013)
Conference and Workshop Papers
- 2024
- [c26]Tim Kaler, Xuhao Chen, Brian Wheatman, Dorothy Curtis, Bruce Hoppe, Tao B. Schardl, Charles E. Leiserson:
Speedcode: Software Performance Engineering Education via the Coding of Didactic Exercises. IPDPS (Workshops) 2024: 391-394 - 2023
- [c25]Helen Xu, Tao B. Schardl, Michael Pellauer, Joel S. Emer:
Optimizing Compression Schemes for Parallel Sparse Tensor Algebra. DCC 2023: 373 - [c24]Helen Xu, Tao B. Schardl, Michael Pellauer, Joel S. Emer:
Optimizing Compression Schemes for Parallel Sparse Tensor Algebra. HPEC 2023: 1-7 - [c23]Tim Kaler, Alexandros-Stavros Iliopoulos, Philip Murzynowski, Tao B. Schardl, Charles E. Leiserson, Jie Chen:
Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching. MLSys 2023 - [c22]Tao B. Schardl, I-Ting Angelina Lee:
OpenCilk: A Modular and Extensible Software Infrastructure for Fast Task-Parallel Code. PPoPP 2023: 189-203 - 2022
- [c21]Yifan Xu, Anchengcheng Zhou, Grace Q. Yin, Kunal Agrawal, I-Ting Angelina Lee, Tao B. Schardl:
Efficient Access History for Race Detection. ALENEX 2022: 117-130 - [c20]Rocío Carratalá-Sáez, Arturo González-Escribano, Alexandros-Stavros Iliopoulos, Charles E. Leiserson, Charlotte Park, Isabel Rosa, Tao B. Schardl, Yuri Torres, David P. Bunde:
Peachy Parallel Assignments (EduHPC 2022). EduHPC@SC 2022: 50-56 - [c19]Tim Kaler, Nickolas Stathas, Anne Ouyang, Alexandros-Stavros Iliopoulos, Tao B. Schardl, Charles E. Leiserson, Jie Chen:
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining. MLSys 2022 - 2021
- [c18]Tim Kaler, Tao B. Schardl, Brian Xie, Charles E. Leiserson, Jie Chen, Aldo Pareja, Georgios Kollias:
PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation. APOCS 2021: 144-158 - [c17]Aaron Handleman, Arthur G. Rattew, I-Ting Angelina Lee, Tao B. Schardl:
A Hybrid Scheduling Scheme for Parallel Loops. IPDPS 2021: 587-598 - [c16]Yifan Xu, Anchengcheng Zhou, Grace Q. Yin, Kunal Agrawal, I-Ting Angelina Lee, Tao B. Schardl:
Efficient Access History for Race Detection. SPAA 2021: 449-451 - 2020
- [c15]Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Tao B. Schardl, Charles E. Leiserson:
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. AAAI 2020: 5363-5370 - [c14]Tim Kaler, William Kuszmaul, Tao B. Schardl, Daniele Vettorel:
Cilkmem: Algorithms for Analyzing the Memory High-Water Mark of Fork-Join Parallel Programs. APOCS 2020: 162-176 - 2019
- [c13]Tao B. Schardl, Siddharth Samsi:
TapirXLA: Embedding Fork-Join Parallelism into the XLA Compiler in TensorFlow Using Tapir. HPEC 2019: 1-8 - 2018
- [c12]Tao B. Schardl, Tyler Denniston, Damon Doucet, Bradley C. Kuszmaul, I-Ting Angelina Lee, Charles E. Leiserson:
The CSI Framework for Compiler-Inserted Program Instrumentation. SIGMETRICS (Abstracts) 2018: 100-102 - [c11]Tao B. Schardl, I-Ting Angelina Lee, Charles E. Leiserson:
Brief Announcement: Open Cilk. SPAA 2018: 351-353 - 2017
- [c10]Tao B. Schardl, William S. Moses, Charles E. Leiserson:
Tapir: Embedding Fork-Join Parallelism into LLVM's Intermediate Representation. PPoPP 2017: 249-265 - 2016
- [c9]Zachary Abel, Erik D. Demaine, Martin L. Demaine, Sarah Eisenstat, Jayson Lynch, Tao B. Schardl:
Who Needs Crossings? Hardness of Plane Graph Rigidity. SoCG 2016: 3:1-3:15 - 2015
- [c8]Tao B. Schardl, Bradley C. Kuszmaul, I-Ting Angelina Lee, William M. Leiserson, Charles E. Leiserson:
The Cilkprof Scalability Profiler. SPAA 2015: 89-100 - [c7]I-Ting Angelina Lee, Tao B. Schardl:
Efficiently Detecting Races in Cilk Programs That Use Reducer Hyperobjects. SPAA 2015: 111-122 - 2014
- [c6]Tim Kaler, William Hasenplaugh, Tao B. Schardl, Charles E. Leiserson:
Executing dynamic data-graph computations deterministically using chromatic scheduling. SPAA 2014: 154-165 - [c5]William Hasenplaugh, Tim Kaler, Tao B. Schardl, Charles E. Leiserson:
Ordering heuristics for parallel graph coloring. SPAA 2014: 166-177 - 2013
- [c4]I-Ting Angelina Lee, Charles E. Leiserson, Tao B. Schardl, Jim Sukha, Zhunping Zhang:
On-the-fly pipeline parallelism. SPAA 2013: 140-151 - 2012
- [c3]Charles E. Leiserson, Tao B. Schardl, Jim Sukha:
Deterministic parallel random-number generation for dynamic-multithreading platforms. PPoPP 2012: 193-204 - 2011
- [c2]Zachary Abel, Erik D. Demaine, Martin L. Demaine, Sarah Eisenstat, Jayson Lynch, Tao B. Schardl, Isaac Shapiro-Ellowitz:
Folding Equilateral Plane Graphs. ISAAC 2011: 574-583 - 2010
- [c1]Charles E. Leiserson, Tao B. Schardl:
A work-efficient parallel breadth-first search algorithm (or how to cope with the nondeterminism of reducers). SPAA 2010: 303-314
Parts in Books or Collections
- 2022
- [p3]Charles E. Leiserson, Tao B. Schardl:
A Work-Efficient Parallel Breadth-First Search Algorithm (or How To Cope With the Nondeterminism of Reducers). Massive Graph Analytics 2022: 3-33 - [p2]William Hasenplaugh, Tim Kaler, Tao B. Schardl, Charles E. Leiserson:
Ordering Heuristics for Parallel Graph Coloring. Massive Graph Analytics 2022: 193-221 - [p1]Tim Kaler, William Hasenplaugh, Tao B. Schardl, Charles E. Leiserson:
Executing Dynamic Data-Graph Computations Deterministically Using Chromatic Scheduling. Massive Graph Analytics 2022: 397-429
Informal and Other Publications
- 2023
- [i7]Tim Kaler, Alexandros-Stavros Iliopoulos, Philip Murzynowski, Tao B. Schardl, Charles E. Leiserson, Jie Chen:
Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching. CoRR abs/2305.03152 (2023) - 2021
- [i6]Tim Kaler, Nickolas Stathas, Anne Ouyang, Alexandros-Stavros Iliopoulos, Tao B. Schardl, Charles E. Leiserson, Jie Chen:
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining. CoRR abs/2110.08450 (2021) - 2019
- [i5]Tao B. Schardl, Siddharth Samsi:
TapirXLA: Embedding Fork-Join Parallelism into the XLA Compiler in TensorFlow Using Tapir. CoRR abs/1908.11338 (2019) - [i4]Tim Kaler, William Kuszmaul, Tao B. Schardl, Daniele Vettorel:
Cilkmem: Algorithms for Analyzing the Memory High-Water Mark of Fork-Join Parallel Programs. CoRR abs/1910.12340 (2019) - 2018
- [i3]Warut Suksompong, Charles E. Leiserson, Tao B. Schardl:
On the Efficiency of Localized Work Stealing. CoRR abs/1804.04773 (2018) - [i2]Mark Weber, Jie Chen, Toyotaro Suzumura, Aldo Pareja, Tengfei Ma, Hiroki Kanezashi, Tim Kaler, Charles E. Leiserson, Tao B. Schardl:
Scalable Graph Learning for Anti-Money Laundering: A First Look. CoRR abs/1812.00076 (2018) - 2017
- [i1]Charles E. Leiserson, Tao B. Schardl, Warut Suksompong:
Upper Bounds on Number of Steals in Rooted Trees. CoRR abs/1706.03184 (2017)
Coauthor Index
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