CC 2022
31st ACM SIGPLAN International Conference on Compiler Construction (CC 2022)
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31st ACM SIGPLAN International Conference on Compiler Construction (CC 2022), April 02–03, 2022, Seoul, South Korea

CC 2022 – Proceedings

Contents - Abstracts - Authors

Frontmatter

Title Page
Welcome from the Chairs
CC 2022 Conference Organization
Sponsors of CC 2022
Report from the Artifact Evaluation Committee

Keynote

Writing and Verifying a Quantum Optimizing Compiler (Keynote)
Robert Rand
(University of Chicago, USA)
Publisher's Version

Quantum Computing and Hardware Design

QSSA: An SSA-Based IR for Quantum Computing
Anurudh Peduri, Siddharth Bhat, and Tobias Grosser
(IIIT Hyderabad, India; University of Edinburgh, UK)
Publisher's Version Artifacts Reusable Results Reproduced
QRANE: Lifting QASM Programs to an Affine IR
Blake Gerard, Tobias Grosser, and Martin Kong
(University of Oklahoma, USA; University of Edinburgh, UK)
Publisher's Version Artifacts Reusable
A Polynomial Time Exact Solution to the Bit-Aware Register Binding Problem
Michael Canesche, Ricardo Ferreira, José Augusto Nacif, and Fernando Magno Quintão Pereira
(Federal University of Minas Gerais, Brazil; Federal University of Viçosa, Brazil)
Publisher's Version

Compiler Theory

Graph Transformations for Register-Pressure-Aware Instruction Scheduling
Ghassan Shobaki, Justin Bassett, Mark Heffernan, and Austin Kerbow
(California State University at Sacramento, USA; Google, USA)
Publisher's Version
Caviar: An E-Graph Based TRS for Automatic Code Optimization
Smail Kourta, Adel Abderahmane Namani, Fatima Benbouzid-Si Tayeb, Kim Hazelwood, Chris Cummins, Hugh Leather, and Riyadh Baghdadi
(NYU Abu Dhabi, United Arab Emirates; École nationale supérieure d'informatique, Algeria; Meta AI, USA)
Publisher's Version Info
On the Computation of Interprocedural Weak Control Closure
Abu Naser Masud and Björn Lisper
(Mälardalen University, Sweden)
Publisher's Version
Seamless Deductive Inference via Macros
Arash Sahebolamri, Thomas Gilray, and Kristopher Micinski
(Syracuse University, USA; University of Alabama at Birmingham, USA)
Publisher's Version Info Artifacts Reusable Results Reproduced

Compilers and Machine Learning

One-Shot Tuner for Deep Learning Compilers
Jaehun Ryu, Eunhyeok Park, and Hyojin Sung
(POSTECH, South Korea)
Publisher's Version Artifacts Functional
Training of Deep Learning Pipelines on Memory-Constrained GPUs via Segmented Fused-Tiled Execution
Yufan Xu, Saurabh Raje, Atanas Rountev, Gerald Sabin, Aravind Sukumaran-Rajam, and P. Sadayappan
(University of Utah, USA; Ohio State University, USA; RNET Technologies, USA; Washington State University, USA)
Publisher's Version Artifacts Reusable Results Reproduced
MLIR-Based Code Generation for GPU Tensor Cores
Navdeep Katel, Vivek Khandelwal, and Uday Bondhugula
(Indian Institute of Science, India; PolyMage Labs, India)
Publisher's Version
Automating Reinforcement Learning Architecture Design for Code Optimization
Huanting Wang, Zhanyong Tang, Cheng Zhang, Jiaqi Zhao, Chris Cummins, Hugh Leather, and Zheng Wang
(NorthWest University, China; University of Leeds, UK; Meta AI, USA)
Publisher's Version Artifacts Reusable Results Reproduced

Parallelism

Memory Access Scheduling to Reduce Thread Migrations
Sana Damani, Prithayan Barua, and Vivek Sarkar
(Georgia Institute of Technology, USA)
Publisher's Version
Performant Portable OpenMP
Guray Ozen and Michael Wolfe
(NVIDIA, Germany; NVIDIA, USA)
Publisher's Version Info

Safety and Correctness

BinPointer: Towards Precise, Sound, and Scalable Binary-Level Pointer Analysis
Sun Hyoung Kim, Dongrui Zeng, Cong Sun, and Gang Tan
(Pennsylvania State University, USA; Xidian University, China)
Publisher's Version
Cape: Compiler-Aided Program Transformation for HTM-Based Cache Side-Channel Defense
Rui Zhang, Michael D. Bond, and Yinqian Zhang
(Ohio State University, USA; Southern University of Science and Technology, China)
Publisher's Version
Making No-Fuss Compiler Fuzzing Effective
Alex Groce, Rijnard van Tonder, Goutamkumar Tulajappa Kalburgi, and Claire Le Goues
(Northern Arizona University, USA; Sourcegraph, USA; Carnegie Mellon University, USA)
Publisher's Version Info Artifacts Functional

Performance Optimizations

Loner: Utilizing the CPU Vector Datapath to Process Scalar Integer Data
Armand Behroozi, Sunghyun Park, and Scott Mahlke
(University of Michigan, USA; NVIDIA Research, USA)
Publisher's Version
Mapping Parallelism in a Functional IR through Constraint Satisfaction: A Case Study on Convolution for Mobile GPUs
Naums Mogers, Lu Li, Valentin Radu, and Christophe Dubach
(University of Edinburgh, UK; University of Sheffield, UK; McGill University, Canada)
Publisher's Version Artifacts Reusable Results Reproduced
Software Pre-execution for Irregular Memory Accesses in the HBM Era
Sanyam Mehta, Gary Elsesser, and Terry Greyzck
(HPE, USA)
Publisher's Version
Efficient Profile-Guided Size Optimization for Native Mobile Applications
Kyungwoo Lee, Ellis Hoag, and Nikolai Tillmann
(Meta, USA)
Publisher's Version

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