akougkas.io
[ io = input/output ]
assistant research professor
data management & storage
distributed & parallel systems
input/output for hpc & ai/ml
illinois tech
chicago, il
i am an assistant research professor in computer science at illinois tech, where i serve as the deputy director of the gnosis research center. my work at illinois tech and as a guest research faculty at argonne national laboratory involves developing cutting-edge data management and storage solutions. with a strong focus on high-performance computing (hpc) and artificial intelligence (ai), i lead innovative projects and guide the next generation of computer scientists. always curious and ready to explore.
*for collaboration opportunities, please reach out via email or linkedin
interests
hpc storage & i/o
- multi-tiered storage architectures, hierarchical data buffering & prefetching, distributed & parallel i/o optimization.
- asynchronous i/o techniques, i/o scheduling strategies, bottleneck detection & optimization, efficient resource utilization.
data management for workflows
- workflow execution optimizations, tiered data streaming engines, context-aware active storage, data prefetching algorithms.
- data management for large datasets, prevention of i/o interference, advanced data compression techniques.
systems for ai & scientific ml
- advanced data management for ai/ml frameworks, ai-driven i/o optimizations, exascale-ready storage.
- integration of ai/ml with hpc systems, context-aware active storage, task-driven frameworks & data labeling.
projects
NEW iowarp
: a state-of-the-art i/o buffering platform for hpc environments, utilizing hdf5 data structures to optimize data placement across memory and storage hierarchies, including nvram and ssds.
hermes
: a state-of-the-art i/o buffering platform for hpc environments, utilizing hdf5 data structures to optimize data placement across memory and storage hierarchies, including nvram and ssds.
iris
: a unified data access framework merging hpc and analytics and ai, enabling integrated data and metadata management, and intelligent data placement.
chronolog
: a high-performance, distributed log storage system that manages activity and log workloads using physical time for event ordering, reducing contention, and enabling elastic scaling across storage tiers. supports plugins, sql-like engines, and tensorflow.
coeus
: a framework that accelerates scientific insights through enriched metadata management, optimizing queries by leveraging ai/ml to balance computation and storage, and enhancing query performance with tiered data placement and staging.
dtio
: a task-driven i/o framework for the hyperconvergence of hpc, ai, and cloud, offering scalable, distributed i/o optimization, enhanced data movement, and improved fault tolerance.
labios
: an innovative, energy-efficient label-based i/o system for multi-tiered hpc environments, providing solutions such as multi-tenancy, resource scheduling, and seamless integration with diverse storage pools.
deepio
: a scalable i/o runtime for ai workflows, optimizing dnn model updates between training and inference tasks. it balances inference quality, training duration, and throughput using novel caching, versioning, and asynchronous data transfer techniques.
contributions
publications: advancing the fields of HPC data management and storage with over 50 peer-reviewed publications.
patents: US patent for the “Label-Based Data Representation I/O Process and System”, US 2021/0374152 A1.
funding: strong track record in funding, successfully securing over $10M of federal grants for my research.
mentoring: co-advising ten doctoral students in data streaming, AI-powered I/O, and programmable storage.
recognition: Best Paper Awards at CCGrid’21 for DLIO and at HPDC’19 for LABIOS papers.
software: deployed open-source software like Hermes, ChronoLog, and DLIO (now in Apache MLPerf suite).
teaching: active learning, engaging teaching environment, emphasizing hands-on, lab-focused experiences.
selected publications
- DLIO: A data-centric benchmark for scientific deep learning applicationsIn 21st International Symposium on Cluster, Cloud and Internet Computing ║ Best Paper Award ║ , May 2021
- Labios: A distributed label-based i/o systemIn 28th International Symposium on High-Performance Parallel and Distributed Computing. ║ Best Paper Award ║ , Jun 2019