activity
20222026
most citedPOSET-RL: Phase ordering for Optimizing Size and Execution Time using Reinforcement Learning

21 citations · 36 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CR2026

Yaksha-Prashna: Understanding eBPF Bytecode Network Function Behavior

Animesh Singh, K Shiv Kumar, S. VenkataKeerthy +7

Many cloud infrastructure organizations increasingly rely on third-party eBPF-based network functions for use cases like security, observability, and load balancing, so that not ev…

cs.SE2025

COFO: COdeFOrces dataset for Program Classification, Recognition and Tagging

Kuldeep Gautam, S. VenkataKeerthy, Ramakrishna Upadrasta

In recent years, a lot of technological advances in computer science have aided software programmers to create innovative and real-time user-friendly software. With the creation of…

cs.PL2023★ 1 cited

VEXIR2Vec: An Architecture-Neutral Embedding Framework for Binary Similarity

S. VenkataKeerthy, Soumya Banerjee, Sayan Dey +5

Binary similarity involves determining whether two binary programs exhibit similar functionality, often originating from the same source code. In this work, we propose VexIR2Vec, a…

cs.PL2023★ 4 cited

The Next 700 ML-Enabled Compiler Optimizations

S. VenkataKeerthy, Siddharth Jain, Umesh Kalvakuntla +6

There is a growing interest in enhancing compiler optimizations with ML models, yet interactions between compilers and ML frameworks remain challenging. Some optimizations require…

cs.PL2022★ 21 cited

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

Shalini Jain, Yashas Andaluri, S. VenkataKeerthy +1

The ever increasing memory requirements of several applications has led to increased demands which might not be met by embedded devices. Constraining the usage of memory in such ca…

cs.LG2022★ 10 cited

RL4ReAl: Reinforcement Learning for Register Allocation

S. VenkataKeerthy, Siddharth Jain, Anilava Kundu +3

We aim to automate decades of research and experience in register allocation, leveraging machine learning. We tackle this problem by embedding a multi-agent reinforcement learning…