Dr. Hariharan Devarajan is a Computer Scientist at Lawrence Livermore National Laboratory and a PhD graduate of Illinois Institute of Technology (2021). As a GRC alumnus, he developed systems including Ares, HFetch, HCompress, HCL, HReplica, Stimulus, and DFTracer. His expertise spans high-performance computing, I/O performance optimization, and distributed storage systems for extreme-scale computing environments.
Joined: Aug 2017Graduated: May 2021
Now: Computer Scientist at Lawrence Livermore National Laboratory
34Publications
1Patents
6Projects
Research Interests
- High Performance Computing
- I/O Performance
- Distributed Storage
- AI-Driven Workflows
Projects
- ChronoLog (2020–2021)
- DeepIO (2021–2022)
- Hermes (2018–2021)
- IRIS (2017–2021)
- LABIOS (2018–2021)
- WisIO (2022–2025)
Publications
2026
Extending I/O Observability to Explainability for Targeted Optimization
2026
Orion: Observability framework for hybrid workflow-centric I/O monitoring in HPC systems
2026
DataCrumbs: Efficient Cross-Layer Data Capture for Explainable I/O Performance in HPC Storage Stacks
2025
Optimizing I/O for an Exascale Implicit Kinetic Plasma Simulation using the Rabbit Storage System
2025
WisIO: Automated I/O Bottleneck Detection with Multi-Perspective Views for HPC Workflows
2024
DFTracer: An Analysis-Friendly Data Flow Tracer for AI-Driven Workflows
2023
Exploring the Impacts of Multiple I/O Metrics in Identifying I/O Bottlenecks
2023
IOMax: Maximizing Out-of-Core I/O Analysis Performance on HPC Systems
2022
A Multifaceted Approach to Automated I/O Bottleneck Detection for HPC Workloads
2022
Stimulus: Accelerate Data Management for Scientific AI applications in HPC
2021
HFlow: A Dynamic and Elastic Multi-Layered Data Forwarder
2021
Apollo: An ML-assisted Real-Time Storage Resource Observer
2021Best Paper Award (First Prize)
DLIO: A Data-Centric Benchmark for Scientific Deep Learning Applications
2020
HReplica: A Dynamic Data Replication Engine with Adaptive Compression for Multi-Tiered Storage
2020
A Dynamic Multi-Tiered Storage System for Extreme Scale Computing
2020
Understanding I/O behavior of Scientific Deep Learning Applications in HPC systems
2020
Bridging Storage Semantics using Data Labels and Asynchronous I/O
2020
ChronoLog: A Distributed Shared Tiered Log Store with Time-based Data Ordering
2020
HCL: Distributing Parallel Data Structures in Extreme Scales
2020
HCompress: Hierarchical Data Compression for Multi-Tiered Storage Environments
2020
HFetch: Hierarchical Data Prefetching for Scientific Workflows in Multi-Tiered Storage Environments
2020
I/O Acceleration via Multi-Tiered Data Buffering and Prefetching
2019
NIOBE: An Intelligent I/O Bridging Engine for Complex and Distributed Workflows
2019
Efficient Data Eviction across Multiple Tiers of Storage
2019
HFetch: Hierarchical Data Prefetching in Multi-Tiered Storage Environments
2019Karsten Schwan Best Paper Award
LABIOS: A Distributed Label-Based I/O System
2019
An Intelligent, Adaptive, and Flexible Data Compression Framework
2018
Vidya: Performing Code-Block I/O Characterization for Data Access Optimization
2018
Harmonia: An Interference-Aware Dynamic I/O Scheduler for Shared Non-Volatile Burst Buffers
2018
Hermes: A Heterogeneous-Aware Multi-Tiered Distributed I/O Buffering System
2018
IRIS: I/O Redirection via Integrated Storage
2017
Open Ethernet Drive: Evolution of Energy-Efficient Storage Technology
2017
Enosis: Bridging the Semantic Gap between File-based and Object-based Data Models
2017