Publications

RL4ReAl: Reinforcement Learning for Register Allocation  

S. VenkataKeerthy, Siddharth Jain, Anilava Kundu, Rohit Aggarwal, Albert Cohen, and Ramakrishna Upadrasta

BullsEye : Scalable and Accurate Approximation Framework for Cache Miss Calculation  

Nilesh Rajendra Shah, Ashitabh misra, Antoine Miné, Rakesh Venkat, and Ramakrishna Upadrasta

Reinforcement Learning assisted Loop Distribution for Locality and Vectorization  

Shalini Jain, S. VenkataKeerthy, Rohit Aggarwal, Tharun Kumar Dangeti, Dibyendu Das, Ramakrishna Upadrasta

Packet Processing Algorithm Identification using Program Embeddings  

S. VenkataKeerthy, Yashas Andaluri, Sayan Dey, Rinku Shah, Praveen Tammana, Ramakrishna Upadrasta

POSET-RL: Phase ordering for Optimizing Size and Execution Time using Reinforcement Learning  

Shalini Jain, Yashas Andaluri, S. VenkataKeerthy, Ramakrishna Upadrasta

OpenMP aware MHP Analysis for Improved Static Data-Race Detection  

Utpal Bora, Shraiysh Vaishay, Saurabh Joshi, Ramakrishna Upadrasta

AI Powered Compiler Techniques for DL Code Optimization  

Sanket Tavarageri, Gagandeep Goyal, Sasikanth Avancha, Bharat Kaul, Ramakrishna Upadrasta

PolyDL: Polyhedral Optimizations for Creation of High Performance DL primitives  

Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul

IR2Vec: A Flow Analysis based Scalable Infrastructure for Program Encodings  

S. VenkataKeerthy, Rohit Aggarwal, Shalini Jain, Maunendra Desarkar, Ramakrishna Upadrasta and Y. N. Srikant

LLOV: A Fast Static Data-Race Checker for OpenMP Programs  

Utpal Bora, Santanu Das, Pankaj Kukreja, Saurabh Joshi, Ramakrishna Upadrasta, Sanjay Rajopadhye

Some Improvements to Branch Probability Information (BPI)  

Akash Banerjee, Rohit Aggarwal, S. VenkataKeerthy and Ramakrishna Upadrasta

An analysis of executable size reduction by LLVM passes  

Shalini Jain, Utpal Bora, Prateek Kumar, Vaibhav B Sinha, Suresh Purini and Ramakrishna Upadrasta

Polyhedral Model Guided Automatic GPU Cache Exploitation Framework  

Abhishek A Patwardhan & Ramakrishna Upadrasta

Some Efficient Algorithms for the Tightest UTVPI Polyhedral Over-Approximation Problem  

Abhishek A Patwardhan & Ramakrishna Upadrasta

Exploiting GPU caches By Polyhedral Compilation

Abhishek A Patwardhan & Ramakrishna Upadrasta

P4LLVM: An LLVM Based P4 Compiler  

Tharun Kumar Dangeti, S. VenkataKeerthy and Ramakrishna Upadrasta

ISL Memory Management Using Clang Static Analyzer  

Malhar Thakkar, Ramakrishna Upadrasta

An LLVM based Loop Profiler  

Shalini Jain, Kamlesh Kumar, Suresh Purini, Dibyendu Das and Ramakrishna Upadrasta

When Polyhedral Optimizations Meet Deep Learning Kernels  

Hrishikesh Vaidya, Akilesh B, Abhishek A Patwardhan, Ramakrishna Upadrasta

Enabling Polyhedral optimizations in TensorFlow through Polly  

Annanay Agarwal, Michael Kruse, Brian Retford, Tobias Grosser and Ramakrishna Upadrasta

Improved Loop Distribution in LLVM using Polyhedral Dependences  

Tharun Kumar Dangeti, Utpal Bora, Santanu Das, Tobias Grosser and Ramakrishna Upadrasta

Implementation of a Cache Miss Calculator in LLVM/Polly  

Keyur Joshi, Ramakrishna Upadrasta, and Albert Cohen

Texturizing PPCG: Supporting Texture Memory in a Polyhedral Compiler  

Abhishek A Patwardhan & Ramakrishna Upadrasta

A Comparative Study of Vectorization in Compilers  

Santanu Das, D. Tharun Kumar, Utpal Bora, Ramakrishna Upadrasta

Polly as an Analysis pass in LLVM  

Utpal Bora, Johannes Doerfert, Tobias Grosser, Venugopal Raghavan and Ramakrishna Upadrasta

Reducing the Computational Complexity of RegionInfo  

Nandini Singhal, Pratik Bhatu, Aditya Kumar, Tobias Grosser, Ramakrishna Upadrasta