Peat, a Python-based Intel-Optimized Tensorflow dockerization with CPU & Memory constraints configurator
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Updated
Aug 5, 2020 - Python
Peat, a Python-based Intel-Optimized Tensorflow dockerization with CPU & Memory constraints configurator
Learned Approximate Matrix Profile (LAMP) implementation on Ultra96-v2 board
Hardware Accelerated Neural Net to classify ecg signals on edge devices
A really fast, secure random file generator. Much faster than /dev/urandom.
An Optimal Microarchitecture for Stencil Computation Acceleration Based on Nonuniform Partitioning of Data Reuse Buffers on FPGAs
This repository contains the findings for scheduling heterogeneous payloads within the Distributed Unit (DU) of a 5G Radio Access Network (RAN)
Aureal A3D Software Development Kit
Verilog implementation of an ordinary differential equation (ODE) solver accelerator chip ― **INCOMPLETE IMPLEMENTATION**
grayscale conversion system and simple convolution system
Hardware Accelerator design for Euler and Modified method in solving ODE using VHDL language in Xilinx Vivado Environment
Innervator: Hardware Acceleration for Neural Networks.
Working 8x8 systolic array hardware implemented in Xilinx Vivado, operated and controlled in software using Xilinx Vitis
Machine Vision Cam Landing Page
A configurable processing element for deep neural network accelerators
Open source RTL simulation acceleration on commodity hardware
A neural network fast inference library implementing Coral Edge TPU emulator using AVX2.
This directory contains the source code for implementing Random Linear Network Coding (RLNC) into Multi-Processor System-on-Chips (MPSoC). By exploiting data vectorization, we obtained latency and throughputs gains during the matrix multiplication operations.
C++ 20 based audio framework
This framework was part of the Diploma thesis titled "Architectures and Implementations of the Neural Network LeNet-5 in FPGAs". The main goal of this thesis was to create a LeNet-5 implementation in an FPGA development board, but also form a reusable framework/workflow which can be modified to model and develop other Neural Networks as well.
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