Martin Kong
Computer Science · The Ohio State University
Publications
46
Citations
533
Est. group size
~1
Recurring co-author estimate
Active years
26
Publishing since 2001
Martin Kong works on compiler and systems techniques for high-performance computing, focusing on how to automatically generate efficient mappings and optimizations for programs running on distributed-memory machines, GPUs, and quantum computers. Much of the work uses mathematical frameworks (affine/polyhedral abstractions) to reason about how computations and data should be distributed and scheduled across many processors or qubits. Students would likely engage with compiler construction, parallel programming models, and applying these optimization ideas to emerging areas like quantum circuit mapping.
Publication output was low in the mid-2010s, spiked in 2021, dipped from 2022-2024, and has picked back up notably in 2025-2026.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Parametric Mappings for Distributed-Memory Tensor Computations - ICS'26 Artifact
Zenodo (CERN European Organization for Nuclear Research) · 2026
- Dependence-Driven, Scalable Quantum Circuit Mapping with Affine Abstractions
2026
- Parametric Mappings for Distributed-Memory Tensor Computations - ICS'26 Artifact
Zenodo (CERN European Organization for Nuclear Research) · 2026
- Portable Anomaly Detection for Distributed PGAS Programs Based on Array Mapping Abstractions
2026
- Parametric Mappings for Distributed-Memory Tensor Computations
2026
- Automatic Generation of Mappings for Distributed Fourier Operations
2025
- Scalable Data-Flow Modeling and Validation of Distributed-Memory Algorithms
2025
- Exploring Communication Anomalies in Chapel
2025
- Generating Two-Level, GPU-Aware Mappings for Distributed Tensor Computations
2025
- Dependence-Driven, Scalable Quantum Circuit Mapping with Affine Abstractions
arXiv (Cornell University) · 2025
- Energy-Aware Tile Size Selection for Affine Programs on GPUs
2024
- QRANE: lifting QASM programs to an affine IR
2022
- OCC: An Automated End-to-End Machine Learning Optimizing Compiler for Computing-In-Memory
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 2021
- On the Impact of Affine Loop Transformations in Qubit Allocation
ACM Transactions on Quantum Computing · 2021
- Tile size selection of affine programs for GPGPUs using polyhedral cross-compilation
2021
- Lecture notes in computer science×4
- arXiv (Cornell University)×4
- Elsevier eBooks×2
- Zenodo (CERN European Organization for Nuclear Research)×2
- IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems×1
- Milind Kulkarni
Computer Science · Purdue University West Lafayette
- Fengguang Song
Computer Science · Indiana University
- Bharath Ramesh
Computer Science · The Ohio State University
- Mahmoud Khairy
Computer Science · Purdue University West Lafayette
- Shulei Xu
Computer Science · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
Claim or correct this profile