HEAM: High-Efficiency Approximate Multiplier Optimization for Deep Neural Networks

Related tags

Deep LearningHEAM
Overview

Approximate Multiplier by HEAM

What's HEAM?

  • HEAM is a general optimization method to generate high-efficiency approximate multipliers for specific applications.
  • This project contains an 8x8 unsigned approximate multiplier based on HEAM for Deep Neural Network (DNN) accelerators and the corresponding Design Compiler(DC) script. Besides, the exact WallaceTree multiplier is included for comparison.

Optimization Procedure of the 8×8 Unsigned Approximate Multiplier

How to compile them?

Make sure that you have installed Design Compiler(DC) and prepared your library files.

compile approximate_multiplier.v

  • step 1: set TOP_LEVEL, all_src, and TOP in scripts/top.tcl at line 1, line 11, and line 15 respectively:
set TOP_LEVEL approximate_multiplier
set all_src "approximate_multiplier.v"
set TOP approximate_multiplier
  • step 2: run commands in terminal:
dc_shell
source scripts/top.tcl

compile wallacetree.v

  • step 1: set TOP_LEVEL, all_src, and TOP in scripts/top.tcl at line 1, line 11, and line 15 respectively:
set TOP_LEVEL wallacetree
set all_src "wallacetree.v"
set TOP wallacetree
  • step 2: run commands in terminal:
dc_shell
source scripts/top.tcl

Experiments of the Approximate Multiplier and the Exact WallaceTree multiplier on Design Compiler(DC) in 3Ghz with a 7-nm Predictive Process Design Kit (PDK) Called the ASAP7 PDK[1]

Ours WallaceTree Reduction
Area ( μm * μm ) 17.52516 42.98184 59.23%
Power ( μW ) 76.2003 151.9432 49.85%

Future

  1. add several reproduced approximate multipliers for comparison;
  2. add DNNs accelerators results.

Reference

[1] Clark, Lawrence T., et al. "ASAP7: A 7-nm finFET predictive process design kit." Microelectronics Journal 53 (2016): 105-115.

Owner
Architecture for Reconfigurable Computing
using STGCN to achieve egg classification task

EEG Classification   The task requires us to classify electroencephalography(EEG) into six categories, including human body, human face, animal body,

4 Jun 13, 2022
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting This is the origin Pytorch implementation of Informer in the followin

Haoyi 3.1k Dec 29, 2022
A user-friendly research and development tool built to standardize RL competency assessment for custom agents and environments.

Built with ❤️ by Sam Showalter Contents Overview Installation Dependencies Usage Scripts Standard Execution Environment Development Environment Benchm

SRI-AIC 1 Nov 18, 2021
The codes and models in 'Gaze Estimation using Transformer'.

GazeTR We provide the code of GazeTR-Hybrid in "Gaze Estimation using Transformer". We recommend you to use data processing codes provided in GazeHub.

65 Dec 27, 2022
Implements a fake news detection program using classifiers.

Fake news detection Implements a fake news detection program using classifiers for Data Mining course at UoA. Description The project is the categoriz

Apostolos Karvelas 1 Jan 09, 2022
Binary Stochastic Neurons in PyTorch

Binary Stochastic Neurons in PyTorch http://r2rt.com/binary-stochastic-neurons-in-tensorflow.html https://github.com/pytorch/examples/tree/master/mnis

Onur Kaplan 54 Nov 21, 2022
LSSY量化交易系统

LSSY量化交易系统 该项目是本人3年来研究量化慢慢积累开发的一套系统,属于早期作品慢慢修改而来,仅供学习研究,回测分析,实盘交易部分未公开

55 Oct 04, 2022
Pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments

Cascaded-FCN This repository contains the pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments the liver and its lesions out of

300 Nov 22, 2022
Code release for Universal Domain Adaptation(CVPR 2019)

Universal Domain Adaptation Code release for Universal Domain Adaptation(CVPR 2019) Requirements python 3.6+ PyTorch 1.0 pip install -r requirements.t

THUML @ Tsinghua University 229 Dec 23, 2022
ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.

ManimML ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.

259 Jan 04, 2023
This source code is implemented using keras library based on "Automatic ocular artifacts removal in EEG using deep learning"

CSP_Deep_EEG This source code is implemented using keras library based on "Automatic ocular artifacts removal in EEG using deep learning" {https://www

Seyed Mahdi Roostaiyan 2 Nov 08, 2022
This repo contains the source code and a benchmark for predicting user's utilities with Machine Learning techniques for Computational Persuasion

Machine Learning for Argument-Based Computational Persuasion This repo contains the source code and a benchmark for predicting user's utilities with M

Ivan Donadello 4 Nov 07, 2022
Structured Edge Detection Toolbox

################################################################### # # # Structure

Piotr Dollar 779 Jan 02, 2023
AI Face Mesh: This is a simple face mesh detection program based on Artificial intelligence.

AI Face Mesh: This is a simple face mesh detection program based on Artificial Intelligence which made with Python. It's able to detect 468 different

Md. Rakibul Islam 1 Jan 13, 2022
Code of paper "Compositionally Generalizable 3D Structure Prediction"

Compositionally Generalizable 3D Structure Prediction In this work, We bring in the concept of compositional generalizability and factorizes the 3D sh

Songfang Han 30 Dec 17, 2022
[ICCV 2021] Group-aware Contrastive Regression for Action Quality Assessment

CoRe Created by Xumin Yu*, Yongming Rao*, Wenliang Zhao, Jiwen Lu, Jie Zhou This is the PyTorch implementation for ICCV paper Group-aware Contrastive

Xumin Yu 31 Dec 24, 2022
This repository provides the code for MedViLL(Medical Vision Language Learner).

MedViLL This repository provides the code for MedViLL(Medical Vision Language Learner). Our proposed architecture MedViLL is a single BERT-based model

SuperSuperMoon 39 Jan 05, 2023
This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".

Graphormer By Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng*, Guolin Ke, Di He*, Yanming Shen and Tie-Yan Liu. This repo is the official impl

Microsoft 1.3k Dec 29, 2022
FluxTraining.jl gives you an endlessly extensible training loop for deep learning

A flexible neural net training library inspired by fast.ai

86 Dec 31, 2022
A python interface for training Reinforcement Learning bots to battle on pokemon showdown

The pokemon showdown Python environment A Python interface to create battling pokemon agents. poke-env offers an easy-to-use interface for creating ru

Haris Sahovic 184 Dec 30, 2022