A work-efficient parallel breadth-first search algorithm (or how to cope with the nondeterminism of reducers). - Charles E. Leiserson; Tao B. Schardl (SPAA, 2010)

Deterministic parallel random-number generation for dynamic-multithreading platforms. - Charles E. Leiserson; Tao B. Schardl; Jim Sukha (PPoPP, 2012)

Folding Equilateral Plane graphs. - Zachary Abel; Erik D. Demaine; Martin L. Demaine; Sarah Eisenstat; Jayson Lynch; Tao B. Schardl; Isaac Shapiro-Ellowitz (Int. J. Comput. Geom. Appl., 2013)

Finding a Hamiltonian Path in a Cube with Specified Turns is Hard. - Zachary Abel; Erik D. Demaine; Martin L. Demaine; Sarah Eisenstat; Jayson Lynch; Tao B. Schardl (J. Inf. Process., 2013)

Ordering heuristics for parallel graph coloring. - William Hasenplaugh; Tim Kaler; Tao B. Schardl; Charles E. Leiserson (SPAA, 2014)

Efficiently Detecting Races in Cilk Programs That Use Reducer Hyperobjects. - I-Ting Angelina Lee; Tao B. Schardl (SPAA, 2015)

The Cilkprof Scalability Profiler. - Tao B. Schardl; Bradley C. Kuszmaul; I-Ting Angelina Lee; William M. Leiserson; Charles E. Leiserson (SPAA, 2015)

On-the-Fly Pipeline Parallelism. - I-Ting Angelina Lee; Charles E. Leiserson; Tao B. Schardl; Zhunping Zhang; Jim Sukha (ACM Trans. Parallel Comput., 2015)

Who Needs Crossings? Hardness of Plane Graph Rigidity. - Zachary Abel; Erik D. Demaine; Martin L. Demaine; Sarah Eisenstat; Jayson Lynch; Tao B. Schardl (SoCG, 2016)

On the efficiency of localized work stealing. - Warut Suksompong; Charles E. Leiserson; Tao B. Schardl (Inf. Process. Lett., 2016)

Upper Bounds on Number of Steals in Rooted Trees. - Charles E. Leiserson; Tao B. Schardl; Warut Suksompong (Theory Comput. Syst., 2016)

Executing Dynamic Data-Graph Computations Deterministically Using Chromatic Scheduling. - Tim Kaler; William Hasenplaugh; Tao B. Schardl; Charles E. Leiserson (ACM Trans. Parallel Comput., 2016)

Performance engineering of multicore software: developing a science of fast code for the post-Moore era. - Tao Benjamin Schardl (2016)

Tapir: Embedding Fork-Join Parallelism into LLVM's Intermediate Representation. - Tao B. Schardl; William S. Moses; Charles E. Leiserson (PPoPP, 2017)

The CSI Framework for Compiler-Inserted Program Instrumentation. - Tao B. Schardl; Tyler Denniston; Damon Doucet; Bradley C. Kuszmaul; I-Ting Angelina Lee; Charles E. Leiserson (Proc. ACM Meas. Anal. Comput. Syst., 2017)

Brief Announcement: Open Cilk. - Tao B. Schardl; I-Ting Angelina Lee; Charles E. Leiserson (SPAA, 2018)

Scalable Graph Learning for Anti-Money Laundering: A First Look. - Mark Weber; Jie Chen 007; Toyotaro Suzumura; Aldo Pareja; Tengfei Ma 001; Hiroki Kanezashi; Tim Kaler; Charles E. Leiserson; Tao B. Schardl (CoRR, 2018)

Efficient Race Detection for Reducer Hyperobjects. - I-Ting Angelina Lee; Tao B. Schardl (ACM Trans. Parallel Comput., 2018)

TapirXLA: Embedding Fork-Join Parallelism into the XLA Compiler in TensorFlow Using Tapir. - Tao B. Schardl; Siddharth Samsi (HPEC, 2019)

Tapir: Embedding Recursive Fork-join Parallelism into LLVM's Intermediate Representation. - Tao B. Schardl; William S. Moses; Charles E. Leiserson (ACM Trans. Parallel Comput., 2019)

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. - Aldo Pareja; Giacomo Domeniconi; Jie Chen 007; Tengfei Ma 001; Toyotaro Suzumura; Hiroki Kanezashi; Tim Kaler; Tao B. Schardl; Charles E. Leiserson (AAAI, 2020)

Cilkmem: Algorithms for Analyzing the Memory High-Water Mark of Fork-Join Parallel Programs. - Tim Kaler; William Kuszmaul; Tao B. Schardl; Daniele Vettorel (APOCS, 2020)

PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation. - Tim Kaler; Tao B. Schardl; Brian Xie; Charles E. Leiserson; Jie Chen 007; Aldo Pareja; Georgios Kollias (APOCS, 2021)

A Hybrid Scheduling Scheme for Parallel Loops. - Aaron Handleman; Arthur G. Rattew; I-Ting Angelina Lee; Tao B. Schardl (IPDPS, 2021)

Ordering Heuristics for Parallel Graph Coloring. - William Hasenplaugh; Tim Kaler; Tao B. Schardl; Charles E. Leiserson (Massive Graph Analytics, 2022)

Executing Dynamic Data-Graph Computations Deterministically Using Chromatic Scheduling. - Tim Kaler; William Hasenplaugh; Tao B. Schardl; Charles E. Leiserson (Massive Graph Analytics, 2022)

A Work-Efficient Parallel Breadth-First Search Algorithm (or How To Cope With the Nondeterminism of Reducers). - Charles E. Leiserson; Tao B. Schardl (Massive Graph Analytics, 2022)

Efficient Access History for Race Detection. - Yifan Xu 007; Anchengcheng Zhou; Grace Q. Yin; Kunal Agrawal 001; I-Ting Angelina Lee; Tao B. Schardl (ALENEX, 2022)

Peachy Parallel Assignments (EduHPC 2022). - Rocío Carratalá-Sáez; Arturo González-Escribano; Alexandros-Stavros Iliopoulos; Charles E. Leiserson; Charlotte Park; Isabel Rosa; Tao B. Schardl; Yuri Torres; David P. Bunde (EduHPC@SC, 2022)

Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining. - Tim Kaler; Nickolas Stathas; Anne Ouyang; Alexandros-Stavros Iliopoulos; Tao B. Schardl; Charles E. Leiserson; Jie Chen 007 (MLSys, 2022)

Optimizing Compression Schemes for Parallel Sparse Tensor Algebra. - Helen Xu 001; Tao B. Schardl; Michael Pellauer; Joel S. Emer (DCC, 2023)

Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching. - Tim Kaler; Alexandros-Stavros Iliopoulos; Philip Murzynowski; Tao B. Schardl; Charles E. Leiserson; Jie Chen 007 (MLSys, 2023)

OpenCilk: A Modular and Extensible Software Infrastructure for Fast Task-Parallel Code. - Tao B. Schardl; I-Ting Angelina Lee (PPoPP, 2023)

Speedcode: Software Performance Engineering Education via the Coding of Didactic Exercises. - Tim Kaler; Xuhao Chen 001; Brian Wheatman; Dorothy Curtis; Bruce Hoppe; Tao B. Schardl; Charles E. Leiserson (IPDPS (Workshops), 2024)

Towards Zero Spawn Overhead: Work Stealing Without Deques. - Aaron Handleman; Kyle Singer; Tao B. Schardl; I-Ting Angelina Lee (SPAA, 2025)