I am a Pre-Doctoral researcher in the TU Wien at the Research Group Parallel Computing. My research interests revolve around the High Performance Computing (HPC) area. Specifically, performance optimization of HPC applications and MPI libraries such as Open MPI and MPICH. My past research includes topics on Interconnects, Resilience and Fault-tolerance.

I developed a new MPI profiling tool called mpisee that follows a new communicator-centric approach to profile MPI applications. In this way, we can explore the use of virtual topology and the impact of MPI communicator mapping on application performance. My current research thesis is focused on the mapping and colocation of parallel applications to deep resource hierarchies that have become more common of HPC systems.

1. Ioannis Vardas, Sascha Hunold, Philippe Swartvagher, and Jesper Larsson Träff: Improved Parallel Application Performance and Makespan by Colocation and Topology-aware Process Mapping, IEEE CCGrid 2024.
2. Ioannis Vardas, Sascha Hunold, Philippe Swartvagher, and Jesper Larsson Träff: Exploring Mapping Strategies for Co-allocated HPC Applications, PhD Symposium of Euro-Par 2023.
3. Ioannis Vardas, Sascha Hunold, Jordy I. Ajanohoun, and Jesper Larsson Träff: mpisee: MPI Profiling for Communication and Communicator Structure, presented at the HIPS Workshop of IPDPS 2022.
4. Ioannis Vardas, Manolis Ploumidis, and Manolis Marazakis: Exploring the impact of node failures on the resource allocation for parallel jobs, 14th Workshop on Resiliency in High Performance Computing (Resilience) in Clusters, Clouds, and Grids.
5. Ioannis Vardas, Manolis Ploumidis, and Manolis Marazakis: Towards Communication Profile, Topology and Node Failure Aware Process Placement, IEE SBAC-PAD 2020.
6. Philippe Swartvagher, Sascha Hunold, Jesper Larsson Träff, and Ioannis Vardas: Using Mixed-Radix Decomposition to Enumerate Computational Resources of Deeply Hierarchical Architectures, presented at the ExaMPI Workshop of SC 2023.
7. Jesper Larsson Träff, and Ioannis Vardas: Library Development with MPI: Attributes, Request Objects, Group Communicator Creation, Local Reductions, and Datatypes, EuroMPI '23.
8. Jesper Larsson Träff, Sascha Hunold, Ioannis Vardas, and Nikolaus Manes Funk: Uniform Algorithms for Reduce-scatter and (most) other Collectives for MPI, IEEE CLUSTER 2023.
9. Sascha Hunold, Jordy I. Ajanohoun, Ioannis Vardas, and Jesper Larsson Träff: An Overhead Analysis of MPI Profiling and Tracing Tools, PERMAVOST 2022.
10. Dimitris Giannopoulos, Nikos Chrysos, Evangelos Mageiropoulos, Giannis Vardas, Leandros Tzanakis, and Manolis Katevenis: Accurate Congestion Control for RDMA Transfers, 2018 IEEE/ACM NOCS.

• FWF-Project Algorithm Engineering for Process Mapping
• European Horizon 2020 project ExaNeSt - European Exascale System Interconnect and Storage
• Green Computing Node for European micro-servers project Euroserver

• YAC SIM a cache memory simulator for a simple one-level cache memory scheme running in command line
• Implementation of RISC-V standard in System Verilog RV32IC