Pinned Repositories
Adiabatic-Logic-Circuits
Our results show that our ASIC implementation of the adiabatic logic circuits outperforms traditional implementations in terms of the proposed design and achieves a performance of 0.16 ns with a 0.8917 µW on-chip power consumption at 29.569 μ^2 chip area.
awesome-neuromorphic-hw
Repository collecting papers about neuromorphic hardware, such as ASIC and FPGA implementations of SNNs and stuff.
CNN-Autoencoder
CompJouleS
Deneme-Repo
ECET-612-Applied-Machine-Learning-
Drexel University ECET-612 Course
gan-hls
Accelerated Image Reconstruction using Generative Adversarial Networks on Cloud FPGAs
HLS-Implementation-of-SVM
We propose an HLS-based implementation of SVMs for classification tasks. We present an optimized architecture for the SVM kernel function, which is a critical component of the algorithm. We also evaluate the performance and accuracy of the proposed design on a range of benchmark datasets.
oscilloscope-vhdl
OTFS_Modulation_FPGA
Muratcanisik4's Repositories
Muratcanisik4/OTFS_Modulation_FPGA
Muratcanisik4/oscilloscope-vhdl
Muratcanisik4/Adiabatic-Logic-Circuits
Our results show that our ASIC implementation of the adiabatic logic circuits outperforms traditional implementations in terms of the proposed design and achieves a performance of 0.16 ns with a 0.8917 µW on-chip power consumption at 29.569 μ^2 chip area.
Muratcanisik4/awesome-neuromorphic-hw
Repository collecting papers about neuromorphic hardware, such as ASIC and FPGA implementations of SNNs and stuff.
Muratcanisik4/CNN-Autoencoder
Muratcanisik4/CompJouleS
Muratcanisik4/Deneme-Repo
Muratcanisik4/ECET-612-Applied-Machine-Learning-
Drexel University ECET-612 Course
Muratcanisik4/gan-hls
Accelerated Image Reconstruction using Generative Adversarial Networks on Cloud FPGAs
Muratcanisik4/HLS-Implementation-of-SVM
We propose an HLS-based implementation of SVMs for classification tasks. We present an optimized architecture for the SVM kernel function, which is a critical component of the algorithm. We also evaluate the performance and accuracy of the proposed design on a range of benchmark datasets.
Muratcanisik4/Muratcanisik4
About me
Muratcanisik4/profile
Muratcanisik4/pyJoules
A Python library to capture the energy consumption of code snippets
Muratcanisik4/SLAC-CompJouleS_NLP