Neeraj Rajesh

I'm a Ph.D. Candidate in Computer Science at Illinois Institute of Technology working on high-performance computing (HPC) I/O optimization and machine learning. I previously did research at IIT's Scalable Computing Software Laboratory working with Dr. Xian-He Sun and Dr. Anthony Kougkas. My work focuses on developing intelligent frameworks to optimize storage systems and I/O performance in HPC environments. My recent research has led to several key contributions including TunIO, an AI-powered framework for optimizing HPC I/O performance through automated parameter tuning, and Apollo, a low-latency ML-assisted monitoring service for storage resources. I'm also working on Viper, a high-performance I/O framework for efficiently managing and transferring deep neural network models.

My research interests span the intersection of HPC systems, storage optimization, and artificial intelligence. I'm passionate about developing novel solutions that leverage machine learning techniques to address performance bottlenecks in large-scale computing systems. My work aims to make HPC storage systems more intelligent, efficient and easier to optimize for complex scientific workloads.

Publications

Viper: A High-Performance I/O Framework for Transparently Updating, Storing, and Transferring Deep Neural Network Models

Viper: A High-Performance I/O Framework for Transparently Updating, Storing, and Transferring Deep Neural Network Models

Jie Ye, J. Cernuda, N. Rajesh, Keith Bateman, Orcun Yildiz, Tom Peterka, Arnur Nigmetov, Dmitriy Morozov, Xian-He Sun, Anthony Kougkas, Bogdan Nicolae

International Conference on Parallel Processing 2024

ABSPDF
TunIO: An AI-powered Framework for Optimizing HPC I/O

TunIO: An AI-powered Framework for Optimizing HPC I/O

N. Rajesh, Keith Bateman, J. L. Bez, Suren Byna, Anthony Kougkas, Xian-He Sun

IEEE International Parallel and Distributed Processing Symposium 2024

ABS
LuxIO: Intelligent Resource Provisioning and Auto-Configuration for Storage Services

LuxIO: Intelligent Resource Provisioning and Auto-Configuration for Storage Services

Keith Bateman, N. Rajesh, Jaime Cernuda Garcia, Luke Logan, Jie Ye, Stephen Herbein, Anthony Kougkas, Xian-He Sun

International Conference on High Performance Computing 2022

ABS
HFlow: A Dynamic and Elastic Multi-Layered I/O Forwarder

HFlow: A Dynamic and Elastic Multi-Layered I/O Forwarder

Jaime Cernuda Garcia, H. Devarajan, Luke Logan, Keith Bateman, N. Rajesh, Jie Ye, Anthony Kougkas, Xian-He Sun

IEEE International Conference on Cluster Computing 2021

ABS
Apollo:: An ML-assisted Real-Time Storage Resource Observer

Apollo:: An ML-assisted Real-Time Storage Resource Observer

N. Rajesh, H. Devarajan, Jaime Cernuda Garcia, Keith Bateman, Luke Logan, Jie Ye, Anthony Kougkas, Xian-He Sun

IEEE International Symposium on High-Performance Parallel Distributed Computing 2020

ABS
Proposed framework for underwater sensor cloud for environmental monitoring

Proposed framework for underwater sensor cloud for environmental monitoring

C. Srimathi, Soo-Hyun Park, N. Rajesh

International Conference on Ubiquitous and Future Networks 2013

ABS

Feature reduction of Darshan counters using evolutionary algorithms

N. Rajesh, Anthony Kougkas, Xian-He Sun, Q. Koziol, Suren Byna, Houjun Tang, J. L. Bez

ChronoLog: A Distributed Shared Tiered Log Store with Time-based Data Ordering

ChronoLog: A Distributed Shared Tiered Log Store with Time-based Data Ordering

Anthony Kougkas, H. Devarajan, Keith Bateman, J. Cernuda, N. Rajesh, Xian-He Sun