Pinned Repositories
-Implementation-of-ANN-to-predict-Handwritten-Language-Using-Verilog
About Implementation of ANN to predict Handwritten Digits using Verilog: Multiplier and Accumulator (MAC), Accumulator(ACC) design, Integrating with sigmoid IP block. Sigmoid is implemented using LUT.
1bit_adder_fpga_verilog
1bit_adder_fpga_verilog
2dconv-FPGA
A 2D convolution hardware implementation written in Verilog
5-Stage-Pipeline-RISC-V-RV32I
The goal of this Project is to design a RISC-V processor with 5 pipeline stages. The version of the RISC-V processor supports only a limited subset of the whole RV32I instruction set, but in the design here reported all the standard instructions except ECALL, EBREAK, and FENCE are implemented.
6T_SRAM
Design, Implementation and Simulation of 6T SRAM Cell under Mixed Signal SOC Design Marathon using eSim & SKY130 by FOSSEE & IITB with Mr. Kunal Ghosh
ACA-CSU_Approximate-Adders
MATLAB and HDL models of ACA-CSU approximate adders
ACArithmeticUnits
Some approximate computing arithmetic units
AccANN
🐆 A compiler from AI model to RTL (Verilog) accelerator in FPGA hardware with auto design space exploration for *AdderNet*
AccDNN
A compiler from AI model to RTL (Verilog) accelerator in FPGA hardware with auto design space exploration.
fifo_hardware_fpga
FIFO implemented on FPGA Spartan 6
mukullokhande99's Repositories
mukullokhande99/AM-Lib_Approx_multipliers
Approx_multipliers
mukullokhande99/Approximate_computing_using_majority_logic
mukullokhande99/ApproximatePrefix
Synthesis of Approximate Parallel Prefix Adders
mukullokhande99/ApproxTrain
mukullokhande99/awesome-approximate-dnn
Curated content for DNN approximation, acceleration ... with a focus on hardware accelerator and deployment
mukullokhande99/Ax-Printed-ML-Classifiers
Approximate Printed Machine Learning Classifiers
mukullokhande99/CapNet-Accelerator
Hardware accelerator for Capsule Neural Networks
mukullokhande99/ComputeLibrary
The Compute Library is a set of computer vision and machine learning functions optimised for both Arm CPUs and GPUs using SIMD technologies.
mukullokhande99/conv_arithmetic
A technical report on convolution arithmetic in the context of deep learning
mukullokhande99/cosa
A scheduler for spatial DNN accelerators that generate high-performance schedules in one shot using mixed integer programming (MIP)
mukullokhande99/dcsr
Software for the paper "dCSR: A Memory-Efficient Sparse Matrix Representation for Parallel Neural Network Inference"
mukullokhande99/dtr-prototype
Dynamic Tensor Rematerialization prototype (modified PyTorch) and simulator. Paper: https://arxiv.org/abs/2006.09616
mukullokhande99/Fixed-Floating-Point-Adder-Multiplier
16-bit Adder Multiplier hardware on Digilent Basys 3
mukullokhande99/handson-ml
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
mukullokhande99/hero
Heterogeneous Research Platform (HERO) for exploration of heterogeneous computers consisting of programmable many-core accelerators and an application-class host CPU, including full-stack software and hardware.
mukullokhande99/LENet
LENet: Lightweight And Efficient LiDAR Semantic Segmentation Using Multi-Scale Convolution Attention
mukullokhande99/Literatures-on-GNN-Acceleration
A reading list for deep graph learning acceleration.
mukullokhande99/MAxPy
MAxPy: A Framework for Bridging Approximate Computing Circuits to its Applications
mukullokhande99/MetaGPT
🌟 The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo
mukullokhande99/NeuroSpector
NeuroSpector: Dataflow and Mapping Optimization of Deep Neural Network Accelerators
mukullokhande99/onnxruntime
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
mukullokhande99/openpiton_fork
The OpenPiton Platform
mukullokhande99/riscv-dnn
A small DNN library for RISC-V, using RISC-V Vector and Matrix extensions
mukullokhande99/RV32-APX
32 Bits RISC-V Processor with Approximate Functions
mukullokhande99/stonne
STONNE: A Simulation Tool for Neural Networks Engines
mukullokhande99/tinyengine
[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory
mukullokhande99/tinyml-papers-and-projects
This is a list of interesting papers and projects about TinyML.
mukullokhande99/torchview
torchview: visualize pytorch models
mukullokhande99/tvm-custom-datatypes-notebook-example
mukullokhande99/yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite