vinodganesan Goto Github PK

compilergym

A reinforcement learning toolkit for compiler optimizations

daa

Practice codes for DAA course

git-flight-rules

Flight rules for git

gsm

Gate-Shift Networks for Video Action Recognition

hardware-aware-transformers

[ACL 2020] HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

imagenet18

Train ImageNet in 18 minutes on AWS

leetcode-1

:pencil: Python / C++ 11 Solutions of All 468 LeetCode Questions

nasbench_tf2.0

neural-networks-on-silicon

This is a collection of works on neural networks and neural accelerators.

neuro-vectorizer

NeuroVectorizer is a framework that uses deep reinforcement learning (RL) to predict optimal vectorization compiler pragmas for for loops in C and C++ codes.

once-for-all-1

[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment

proxylessnas

[ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

riscv-tests

shaktifpu

This repository contains the codebase of Floating Point Unit used in different variants of the SHAKTI Processor effort

shaktisim

This archived codebase is a simple RISC-V Instruction Set Simulator designed to verify SHAKTI cores

simpleslide

spatial-tuts

temporal-shift-module

[ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding

trn-pytorch

Temporal Relation Networks

vector-accelerator

This is an archived repository of an older version of Vector Processor (based on Berkeley's Hwacha) designed at SHAKTI group IIT Madras

vinodganesan.github.io