Georgios Smaragdos
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Dr.Ir. Georgios Smaragdos

  • Position: PhD, Research Technician, Erasmus MC
  • Member of:

Biography

Georgios Smaragdos was born in Thessaloniki, Greece, on July 3rd 1983. After participating in the national examinations for a university admission, he was admitted to the Technical University of Crete (TUC), in Chania, in the department of Electronics & Computer Engineering (5 year Diploma). The title of his Diploma Thesis was ”Design Of Current Mode CMOS Integrated Filters ” and was concluded under the supervision of Matthias Bucher. He obtained his Master degree from Delft University of Technology in July 2012. His Master Thesis ( " An Adaptive Defect-Tolerant Multiprocessor Array Architecture ") was completed under the supervision of Yiannis Sourdis and Christos Strydis. On March 2024 he obtained his PhD degree with the thesis titled "BrainFrame: From FPGA to heterogeneous acceleration of brain simulations" in the Erasmus MC Neuroscience Department. He is currently a Research Technician and Systems Administrator at the Erasmus MC Neuroscience Dept.

Research Interests

  1. Reconfigurable hardware
  2. Computer Architecture
  3. High Performance Computing
  4. Scientific Computing
  5. Embedded Systems

Education

2024

PhD

in Neuroscience Department, Erasmus MC

2012

Master of Science

in Computer Engineering Delft University of Technology

2012

5 year Engineering Diploma

in Electronics Engineering Technical University of Crete

Honors & Awards

2016

Best Paper Nomination

ISPASS 2016

2016

HPC Cross-Site Collaboration Grant

EuroLab

Publications

1. A Reconfigurable Architecture of a Scalable, Ultrafast, Ultrasound, Delay-and-Sum Beamformer.

Vasilis Kypriotis, Georgios Smaragdos, Pieter Kruizinga, Dimitrios Soudris, Christos Strydis
in 2024
DOI: 10.1109/IPDPSW63119.2024.00050

2. Synthesis-Free, Flexible and Fast Hardware Library for Biophysically Plausible Neurosimulations - POSTER

Rene Miedema, Georgios Smaragdos, Mario Negrello, Zaid Al-Ars, Matthias Möller, and Christos Strydis
in FPGA '20: The 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays 2020
DOI: 10.1145/3373087.3375374

3. flexHH: A Flexible Hardware Library for Hodgkin-Huxley-Based Neural Simulations

Miedema R, Smaragdos G, Negrello M, Al-Ars Z, Möller M, Strydis C
in IEEE Access 2020
DOI: https://dx.doi.org/10.1109/ACCESS.2020.3007019

4. A novel simulator for extended Hodgkin-Huxley neural networks.

Sotirios Panagiotou, Rene Miedema, Harry Sidiropoulos, Georgios Smaragdos, Christos Strydis, Dimitrios Soudris
in 2020
DOI: 10.1109/BIBE50027.2020.00071

5. Multinode implementation of an extended Hodgkin-Huxley simulator.

George Chatzikonstantis, Harry Sidiropoulos, Christos Strydis, Mario Negrello, Georgios Smaragdos, Chris I. De Zeeuw, Dimitrios Soudris
in Neurocomputing 2019
DOI: 10.1016/J.NEUCOM.2018.10.062

6. Prototyping a Biologically Plausible Neuron Model on a Heterogeneous CPU-FPGA Board.

Kaleb Alfaro-Badilla, Alfonso Chacon-Rodriguez, Georgios Smaragdos, Christos Strydis, Andres Arroyo-Romero, Javier Espinoza-Gonzalez, Carlos Salazar-Garcia
in 2019 IEEE 10th Latin American Symposium on Circuits & Systems 2019
DOI: 10.1109/LASCAS.2019.8667538

7. Exploring Complex Brain-Simulation Workloads on Multi-GPU Deployments

Michiel A. van der Vlag , Georgios Smaragdos , Zaid Al-Ars , Christos Strydis
in ACM Transactions on Architecture and Code Optimization (TACO) 2019
DOI: 10.1145/3371235

8. GPU Implementation of Neural-Network Simulations based on Adaptive-Exponential Models

A. Neofytou, G. Chatzikostantis, I Magkanaris, G. Smaragdos, C. Strydis, D. Soudris
in IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE) 2019
DOI: 10.1109/BIBE.2019.00067

9. Improving the Simulation of Biologically Accurate Neural Networks Using Data Flow HLS Transformations on Heterogeneous SoC-FPGA Platforms

K. Alfaro-Badilla, A. Arroyo-Romero, C. Salazar-García, L.G.L. Vega, J. Espinoza-González, F. Hernández- Castro, A. Chacón-Rodríguez, G. Smaragdos, C. Strydis
in CARLA 2019: High Performance Computing 2019
DOI: 10.1007/978-3-030-41005-6_13

10. A Real-Time Reconfigurable Multichip Architecture for Large-Scale Biophysically Accurate Neuron Simulation.

Amir Zjajo, Jaco Hofmann, Gerrit Jan Christiaanse, Martijn F. van Eijk, Georgios Smaragdos, Christos Strydis, Alexander de Graaf, Carlo Galuzzi, Rene van Leuken
in IEEE Trans. Biomed. Circuits and Systems 2018
DOI: 10.1109/TBCAS.2017.2780287
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