No Class (Wednesday, Mar 22, 2023): Work on Projects
Class 17 (Monday, Mar 27, 2023): Research Paper Presentations I
Viraj Lunani, Vedant Iyer, Wei-Lun Huang, Taeyoon Kim, and Aayush Singh (Group 5), "Detection & Mitigation of Ciphertext Side-Channels in Trusted Execution Environments" - Slides;Paper1;Paper2
Ian Iong Lam, Jiayao Su, Tony Tang (Group 2), "Optimized Unrolling of Nested Loops" - Slides;Paper
Class 18 (Wednesday, Mar 29, 2023): Research Paper Presentations II
Hustin Cao, Aylin Gunal, and Shinka Mori (Group 1), "Towards Neural Architecture-Aware Exploration Of Compiler Optimizations in a Deep Learning {Graph} Compiler" - Slides;Paper
Braden Crimmins, Matthew Ruiz, and Alan Yang (Group 9), "AddressSanitizer: A Fast Address Sanity Checker" - Slides;Paper
Qiping Pan, Ruizhe Deng, Zhuocheng Sun, and Hongxi Pu (Group 4), "IntPatch: Automatically Fix Integer-Overflow-to-Buffer-Overflow Vulnerability at Compile-Time " - Slides;Paper
Class 19 (Monday, Apr 3, 2023): Research Paper Presentations III
Alec Korotney, Vijairam, Viroshan Narayan, and Ibrahim Abouarabi (Group 11), "Optimizing Loop Fusion" - Slides;Paper
Siqi Shao, Yixin Shi, and Ying Yang (Group 15), "Deep reinforcement learning in loop fusion problem" - Slides;Paper
Class 20 (Wednesday, Apr 5, 2023): Research Paper Presentations IV
Anna Li, Ruipu Li, Tianchen Ye, and Yuqi Li (Group 12), "Predicting Unroll Factors Using Supervised Classification" - Slides;Paper
Z. Wang, M. Yuan, Z. Zhang, and Z. Zhou (Group 7), "A Loop Transformation Theory and an Algorithm to Maximize Parallelism" - Slides;Paper
Xuweiyi Chen, Jiaming Zheng, Congming Liao, and Zin Hu (Group 3), "MLGO: A Machine Learning Guided Compiler Optimizations Framework" - Slides;Paper
Zheyu Zhang, Yunchi Lu, and Xueming Xu (Group 6), "PROGRAML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations" - Slides;Paper
Class 21 (Monday, Apr 10, 2023): Research Paper Presentations V
Zhenning Yang, Reggie Hsu, Leo Wu, and Dave Yonkers (Group 14), "TVM: An Automated End-to-End Optimizing Compiler for Deep Learning" - Slides;Paper
Matt Martin, Luke Hobeika, and Jason Qian (Group 13), "Bringing the Web Up to Speed with Webassembly" - Slides;Paper
Zhixiang Teoh, Peter Ly, Owen Goebel, and Neel Shah (Group 10), "ACCEPT: A Programmer-Guided Compiler Framework for Practical Approximate Computing" - Slides;Paper
Jiyu Chen, Jihong Gan, Yuchen Jiang, and Daniel Mishins (Group 16), "MLIR: Scaling Compiler Infrastructure for
Domain Specific Computation" - Slides;Paper