I'm currently studying Electrical and Computer Engineering at University of Thessaly in Volos, Greece.
Currently I am working on rl4hls, a project that aims to optimize the deployment of neural networks on FPGAs through optimizations like quantization and prunning, using reinforcement learning.
- C
- C++
- Python
- Verilog
- MATLAB
- CUDA
- OpenMP
- MPI
- Xilinx Vivado
- Xilinx Vitis HLS
- TensorFlow
- PyTorch
- Bash
- Make
- Linux
- Git & Github
- VTune Profiler
- Efficient Deep Learning
- Neural Network Quantization & Pruning
- FPGA/Hardware Accelerators
- Reinforcement Learning for Systems Optimization
- TinyML and Edge AI
Parallel K-Means clustering using OpenMP, 2D seperable convolution using CUDA, image histogram equalization using OpenMP/CUDA, N-Body simulation using OpenMP/CUDA.
An optimized implementation of the Smith-Waterman algorithm for local sequence alignment on an FPGA.
Implemented a complete circuit simulation program like SPICE in C++. Implemented parsing, equation formulation, and solution techniques (direct and iterative) for linear circuits. Utilized sparse matrix techniques and external libraries (Eigen) for efficient computation.
Designed, simulated, and implemented a Floating Point Unit on a Zedboard FPGA.