I am an Assistant Professor in the Computer Science Department at the University of Crete, and a Guest Researcher at the Computer Architecture and VLSI Systems Laboratory of the Institute of Computer Science of the Foundation for Research and Technology - Hellas. My research interests include Concurrency and Programming Languages and Big Data Analytics.

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Research

My research aims to develop tools and systems for the development and efficient execution of parallel and distributed software. I am interested in programming languages, software engineering, type systems and static analysis, and their applications on concurrent and distributed software, and in particular scientific and big data computations.

Projects

In the EuroEXA project, I work on programming models and runtime systems that facilitate the development, distribution, and scaling of exascale applications to novel hardware. In the ETAK project, I work on automating the deployment and efficient scheduling of earthquake and building simulations as services hosted in the cloud.

Past Projects

I coordinated Project ASAP, which focused on designing, developing, modeling, and efficiently scheduling big data analytics workflows. The project finished successfully and was rated ``excellent''. Myrmics, BDDT, and PARTEE are task-parallel runtimes for distributed-memory, non cache coherent shared memory and cache coherent shared memory multicore processors that scale parallel applications to tens or hundreds of cores. GreenVM is a Java Virtual Machine for distributed memory manycores running on the 512-core Formic prototype.

Software Fault Tolerance

An error in a single core of a 64-core or 512-core parallel processor should not cause the whole system to malfunction. We design and build software systems that can recover from soft-errors and hard-errors, focusing on multicore processors. We are using traditional techniques like checkpointing and redundancy, combining them with high-level abstractions like task-parallel programming that help make fault-tolerance very efficient.

Static Analysis and Compilation

We implemented several static analyses that take advantage of high-level abstractions in parallel programming languages like regions and tasks, to efficiently compile these programs to multicore processors and distributed systems.

Teaching

Students, Supervised or Co-Supervised

Current

Past