Publications
Publications from the last few years are listed below. For older publications, please refer to DBLP, Google Scholar, and my CV.
CoNST: Code Generator for Sparse Tensor Networks, Saurabh Raje, Yufan Xu, Atanas Rountev, Edward Valeev, and P. Sadayappan. ACM Transactions on Architecture and Code Optimization (ACM TACO), volume 21, article 82, pages 1-24, November 2024. [pdf]
Automatic Generation of Distributed-Memory Mappings for Tensor Computations, Martin Kong, Raneem Abu Yosef, Atanas Rountev, and P. Sadayappan. International Conference for High Performance Computing Networking, Storage, and Analysis (SC), November 2023. [pdf]
Differential Privacy for Analysis of Software Traces, Yu Hao. Ph.D. Thesis, Ohio State University, August 2023. [pdf] [artifact1] [artifact2]
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. ACM SIGPLAN International Conference on Compiler Construction (CC), April 2022. [pdf]
Comprehensive Accelerator-Dataflow Co-design Optimization for Convolutional Neural Networks, Miheer Vaidya, Aravind Sukumaran-Rajam, Atanas Rountev, and P. Sadayappan. International Symposium on Code Generation and Optimization (CGO), April 2022. [pdf]
Introducing Differential Privacy Mechanisms for Mobile App Analytics of Dynamic Content, Sufian Latif. Ph.D. Thesis, Ohio State University, December 2021. [pdf]
Brief Announcement: Efficient Distributed Algorithms for Convolutional Neural Networks, Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, and P. Sadayappan. ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), July 2021. [pdf]
Differential Privacy for Coverage Analysis of Software Traces, Yu Hao*, Sufian Latif*, Hailong Zhang, Raef Bassily, and Atanas Rountev (*co-leads with equal contributions). European Conference on Object-Oriented Programming (ECOOP), July 2021. [pdf] [artifact]
IOOPT: Automatic Derivation of I/O Complexity Bounds for Affine Programs, Auguste Olivry, Guillaume Iooss, Nicolas Tollenaere, Atanas Rountev, P. Sadayappan, and Fabrice Rastello. ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), June 2021. [pdf]
Analytical Characterization and Design Space Exploration for Optimization of CNNs, Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, and P. Sadayappan. ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), April 2021. [pdf]
Differentially-Private Software Frequency Profiling under Linear Constraints, Hailong Zhang, Yu Hao, Sufian Latif, Raef Bassily, and Atanas Rountev. ACM SIGPLAN Conference on Systems, Programming, Languages, and Applications: Software for Humanity (SPLASH/OOPSLA), November 2020. [pdf] [artifact]
Introducing Differential Privacy Mechanisms for Mobile App Analytics of Dynamic Content, Sufian Latif, Yu Hao, Hailong Zhang, Raef Bassily, and Atanas Rountev. IEEE International Conference on Software Maintenance and Evolution (ICSME), September 2020. [pdf] [artifact]
Differentially-Private Control-Flow Node Coverage for Software Usage Analysis, Hailong Zhang, Sufian Latif, Raef Bassily, and Atanas Rountev. USENIX Security Symposium, August 2020. [pdf] [artifact]
Differentially-Private Remote Software Profiling, Hailong Zhang. Ph.D. Thesis, Ohio State University, July 2020. [pdf]
Sentinel: Generating GUI Tests for Sensor Leaks in Android and Android Wear Apps, Haowei Wu*, Hailong Zhang*, Yan Wang, and Atanas Rountev (*co-leads with equal contributions). Software Quality Journal, March 2020. [pdf]
A Study of Event Frequency Profiling with Differential Privacy, Hailong Zhang, Yu Hao, Sufian Latif, Raef Bassily, and Atanas Rountev. ACM SIGPLAN International Conference on Compiler Construction (CC), February 2020. [pdf]