CGO 2020
18th ACM/IEEE International Symposium on Code Generation and Optimization (CGO)
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18th ACM/IEEE International Symposium on Code Generation and Optimization (CGO), February 22–26, 2020, San Diego, CA, USA

CGO 2020 – Proceedings

Contents - Abstracts - Authors

Frontmatter

Title Page
Welcome form the Steering Committee
Message from the Program Chairs
CGO 2020 Organization
Report from the Artifact Evaluation Committee
Sponsors

Dynamic Languages

Efficient Nursery Sizing for Managed Languages on Multi-core Processors with Shared Caches
Mohamed Ismail and G. Edward Suh
(Cornell University, USA)
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Type Freezing: Exploiting Attribute Type Monomorphism in Tracing JIT Compilers
Lin Cheng, Berkin Ilbeyi, Carl Friedrich Bolz-Tereick, and Christopher Batten
(Cornell University, USA; University of Düsseldorf, Germany)
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Safety and Reliability

Low-Cost Prediction-Based Fault Protection Strategy
Sunghyun Park, Shikai Li, Ze Zhang, and Scott Mahlke
(University of Michigan, USA)
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Secure Automatic Bounds Checking: Prevention Is Simpler Than Cure
Ejebagom John Ojogbo, Mithuna Thottethodi, and T. N. Vijaykumar
(Purdue University, USA)
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Aloe: Verifying Reliability of Approximate Programs in the Presence of Recovery Mechanisms
Keyur Joshi, Vimuth Fernando, and Sasa Misailovic
(University of Illinois at Urbana-Champaign, USA)
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Interactive Debugging of Concurrent Programs under Relaxed Memory Models
Aakanksha Verma, Pankaj Kumar Kalita, Awanish Pandey, and Subhajit Roy
(IIT Kanpur, India)
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Best Paper Finalists

Testing Static Analyses for Precision and Soundness
Jubi Taneja, Zhengyang Liu, and John Regehr
(University of Utah, USA)
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HALO: Post-Link Heap-Layout Optimisation
Joe Savage and Timothy M. Jones
(University of Cambridge, UK)
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Efficient and Scalable Cross-ISA Virtualization of Hardware Transactional Memory
Wenwen Wang, Pen-Chung Yew, Antonia Zhai, and Stephen McCamant
(University of Georgia, USA; University of Minnesota, USA)
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GPUs

Speculative Reconvergence for Improved SIMT Efficiency
Sana Damani, Daniel R. Johnson, Mark Stephenson, Stephen W. Keckler, Eddie Yan, Michael McKeown, and Olivier Giroux
(Georgia Institute of Technology, USA; NVIDIA, USA; University of Washington, USA; Esperanto Technologies, USA)
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Optimizing Occupancy and ILP on the GPU using a Combinatorial Approach
Ghassan Shobaki, Austin Kerbow, and Stanislav Mekhanoshin
(California State University at Sacramento, USA; Advanced Micro Devices, USA)
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Compilation for Specialized Domains

Multi-layer Optimizations for End-to-End Data Analytics
Amir Shaikhha, Maximilian Schleich, Alexandru Ghita, and Dan Olteanu
(University of Oxford, UK)
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Optimizing Ordered Graph Algorithms with GraphIt
Yunming Zhang, Ajay Brahmakshatriya, Xinyi Chen, Laxman Dhulipala, Shoaib Kamil, Saman Amarasinghe, and Julian Shun
(Massachusetts Institute of Technology, USA; Carnegie Mellon University, USA; Adobe Research, USA)
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A Performance-Optimizing Compiler for Cyber-Physical Digital Microfluidic Biochips
Tyson Loveless, Jason Ott, and Philip Brisk
(University of California at Riverside, USA)
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CogniCryptGEN: Generating Code for the Secure Usage of Crypto APIs
Stefan Krüger, Karim Ali, and Eric Bodden
(University of Paderborn, Germany; University of Alberta, Canada; Fraunhofer IEM, Germany)
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Tool and Practical Experience Papers

AN5D: Automated Stencil Framework for High-Degree Temporal Blocking on GPUs
Kazuaki Matsumura, Hamid Reza Zohouri, Mohamed Wahib, Toshio Endo, and Satoshi Matsuoka
(Barcelona Supercomputing Center, Spain; Edgecortix, Japan; AIST, Japan; Tokyo Institute of Technology, Japan; RIKEN CCS, Japan)
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The Design and Implementation of the Wolfram Language Compiler
Abdul Dakkak, Tom Wickham-Jones, and Wen-mei Hwu
(University of Illinois at Urbana-Champaign, USA; Wolfram Research, UK)
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SIMD Support in .NET: Abstract and Concrete Vector Types and Operations
Carol Eidt and Tanner Gooding
(Microsoft, USA)
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Code Optimization

NeuroVectorizer: End-to-End Vectorization with Deep Reinforcement Learning
Ameer Haj-Ali, Nesreen K. Ahmed, Ted Willke, Yakun Sophia Shao, Krste Asanovic, and Ion Stoica
(University of California at Berkeley, USA; Intel Labs, USA)
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Introducing the Pseudorandom Value Generator Selection in the Compilation Toolchain
Michael Leonard and Simone Campanoni
(Northwestern University, USA)
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Heterogeneity and Parallelism

COLAB: A Collaborative Multi-factor Scheduler for Asymmetric Multicore Processors
Teng Yu, Pavlos Petoumenos, Vladimir Janjic, Hugh Leather, and John Thomson
(University of St. Andrews, UK; University of Manchester, UK; University of Edinburgh, UK)
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PreScaler: An Efficient System-Aware Precision Scaling Framework on Heterogeneous Systems
Seokwon Kang, Kyunghwan Choi, and Yongjun Park
(Hanyang University, South Korea)
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ATMem: Adaptive Data Placement in Graph Applications on Heterogeneous Memories
Yu Chen, Ivy B. Peng, Zhen Peng, Xu Liu, and Bin Ren
(College of William and Mary, USA; Lawrence Livermore National Laboratory, USA)
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Code Generation and Transformation

Automatic Generation of High-Performance Quantized Machine Learning Kernels
Meghan Cowan, Thierry Moreau, Tianqi Chen, James Bornholt, and Luis Ceze
(University of Washington, USA; University of Texas at Austin, USA)
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Deriving Parametric Multi-way Recursive Divide-and-Conquer Dynamic Programming Algorithms using Polyhedral Compilers
Mohammad Mahdi Javanmard, Zafar Ahmad, Martin Kong, Louis-Noël Pouchet, Rezaul Chowdhury, and Robert Harrison
(Stony Brook University, USA; University of Oklahoma, USA; Colorado State University, USA)
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