Ramakrishna Upadrasta

According to our database, Ramakrishna Upadrasta authored at least 25 papers between 2000 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

The Next 700 ML-Enabled Compiler Optimizations.

S. VenkataKeerthy, Siddharth Jain, Umesh Kalvakuntla, Pranav Sai Gorantla, Rajiv Shailesh Chitale, Eugene Brevdo, Albert Cohen, Mircea Trofin, Ramakrishna Upadrasta

Proceedings of the 33rd ACM SIGPLAN International Conference on Compiler Construction, 2024

2023

BullsEye : Scalable and Accurate Approximation Framework for Cache Miss Calculation.

Nilesh Rajendra Shah, Ashitabh Misra, Antoine Miné, Rakesh Venkat, Ramakrishna Upadrasta

ACM Trans. Archit. Code Optim., March, 2023

VEXIR2Vec: An Architecture-Neutral Embedding Framework for Binary Similarity.

S. VenkataKeerthy, Yashas Andaluri, Sayan Dey, Soumya Banerjee, Ramakrishna Upadrasta

CoRR, 2023

RL4ReAl: Reinforcement Learning for Register Allocation.

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

Proceedings of the 32nd ACM SIGPLAN International Conference on Compiler Construction, 2023

2022

RL4ReAl: Reinforcement Learning for Register Allocation.

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

CoRR, 2022

FUSED-PAGERANK: Loop-Fusion based Approximate PageRank.

Shalini Jain, Rahul Utkoor, Hemalatha Eedi, Sathya Peri, Ramakrishna Upadrasta

CoRR, 2022

Reinforcement Learning assisted Loop Distribution for Locality and Vectorization.

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

Proceedings of the Eighth IEEE/ACM Workshop on the LLVM Compiler Infrastructure in HPC, 2022

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

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

Proceedings of the International IEEE Symposium on Performance Analysis of Systems and Software, 2022

Packet Processing Algorithm Identification using Program Embeddings.

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

Proceedings of the 6th Asia-Pacific Workshop on Networking, 2022

Advanced Construction Algorithms for SSA.

Dibyendu Das, Ramakrishna Upadrasta, Vugranam C. Sreedhar

Proceedings of the SSA-based Compiler Design, 2022

2021

PolyDL: Polyhedral Optimizations for Creation of High-performance DL Primitives.

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

ACM Trans. Archit. Code Optim., 2021

AI Powered Compiler Techniques for DL Code Optimization.

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

CoRR, 2021

OpenMP aware MHP Analysis for Improved Static Data-Race Detection.

Utpal Bora, Shraiysh Vaishay, Saurabh Joshi, Ramakrishna Upadrasta

Proceedings of the 7th IEEE/ACM Workshop on the LLVM Compiler Infrastructure in HPC, 2021

2020

IR2VEC: LLVM IR Based Scalable Program Embeddings.

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

ACM Trans. Archit. Code Optim., 2020

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

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

ACM Trans. Archit. Code Optim., 2020

PolyScientist: Automatic Loop Transformations Combined with Microkernels for Optimization of Deep Learning Primitives.

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

CoRR, 2020

2019

IR2Vec: A Flow Analysis based Scalable Infrastructure for Program Encodings.

Venkata Keerthy S, Rohit Aggarwal, Shalini Jain, Maunendra Sankar Desarkar, Ramakrishna Upadrasta, Y. N. Srikant

CoRR, 2019

Polyhedral Model Guided Automatic GPU Cache Exploitation Framework.

Abhishek A. Patwardhan, Ramakrishna Upadrasta

Proceedings of the 17th International Conference on High Performance Computing & Simulation, 2019

2018

P4LLVM: An LLVM Based P4 Compiler.

Tharun Kumar Dangeti, Venkata Keerthy S, Ramakrishna Upadrasta

Proceedings of the 2018 IEEE 26th International Conference on Network Protocols, 2018

2013

Sub-Polyhedral Compilation using (Unit-)Two-Variables-Per-Inequality Polyhedra. (Compilation sous-polyédrique reposant sur des systèmes à deux variables par inégalité).

Ramakrishna Upadrasta

PhD thesis, 2013

Sub-polyhedral scheduling using (unit-)two-variable-per-inequality polyhedra.

Ramakrishna Upadrasta, Albert Cohen

Proceedings of the 40th Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, 2013

2012

Efficient liveness computation using merge sets and DJ-graphs.

Dibyendu Das, Benoît Dupont de Dinechin, Ramakrishna Upadrasta

ACM Trans. Archit. Code Optim., 2012

2005

A practical and fast iterative algorithm for phi-function computation using DJ graphs.

Dibyendu Das, U. Ramakrishna

ACM Trans. Program. Lang. Syst., 2005

Combined ILP and Register Tiling: Analytical Model and Optimization Framework.

Lakshminarayanan Renganarayanan, U. Ramakrishna, Sanjay V. Rajopadhye

Proceedings of the Languages and Compilers for Parallel Computing, 2005

2000

Extending Graham-Glanville techniques for optimal code generation.

Maya Madhavan, Priti Shankar, Siddhartha Rai, U. Ramakrishna

ACM Trans. Program. Lang. Syst., 2000