Energy consumption estimation utilities for Jetson-based platforms

Overview

jetson_power

Energy consumption estimation utilities for Jetson-based platforms

This repository contains a utility for measuring energy consumption when running various programs in NVIDIA Jetson-based platforms. Currently TX-2, NX, and AGX are supported.

Usage

If you want to measure the energy consumption of a program, you can directly run the utility providing the command that you want to measure:

./p_est program_to_run

You can test the utility using a stress test (make sure you have installed stress - apt install stress), e.g.,

./p_est stress --cpu 6 -t 5

You can also run a GPU-based test using CUDA examples:

sudo make  /usr/local/cuda-10.2/samples/0_Simple/matrixMul/matrixMul
./p_est.py /usr/local/cuda-10.2/samples/0_Simple/matrixMul/matrixMul -wA=9200 -hA=320 -wB=640 -hB=9200

You can play around jetson_clocks.sh and see the consumption indeed increasing.

Interfacing with Python for more precise measurements

Using the utility from the command line can include initialization cost in the power consumption. Even though this can be estimated and then subtracted, we also provide a simple Python API:

from p_est import PowerEstimator
from time import sleep

def my_fun():
    for i in range(5):
        sleep(1)
        print('sleeping')


p_est = PowerEstimator()
total_energy, total_energy_over_idle, total_time = p_est.estimate_fn_power(my_fun)

You can use the PowerEstimator class to directly measure the energy consumption of any function.

Things to consider

  • Currently, the tool has been tested only on AGX. Testing is pending on NX and TX2.
  • If sensors report overlapping power measurements, then the tools might overestimate power usage.
  • Power usage is estimated solely using the sensors provided by Jetsons. This usually underestimates the total power.
  • You can consider increasing sampling rate in order to have more precise measurements.
Owner
OpenDR
OpenDR H2020 Research Project
OpenDR
Walk with fastai

Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Walk with fastai What is this p

Walk with fastai 124 Dec 10, 2022
Tree Nested PyTorch Tensor Lib

DI-treetensor treetensor is a generalized tree-based tensor structure mainly developed by OpenDILab Contributors. Almost all the operation can be supp

OpenDILab 167 Dec 29, 2022
DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data.

DeepConsensus DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS)

Google 149 Dec 19, 2022
Trustworthy AI related projects

Trustworthy AI This repository aims to include trustworthy AI related projects from Huawei Noah's Ark Lab. Current projects include: Causal Structure

HUAWEI Noah's Ark Lab 589 Dec 30, 2022
A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.

Rockpool Rockpool is a Python package for developing signal processing applications with spiking neural networks. Rockpool allows you to build network

SynSense 21 Dec 14, 2022
Collect some papers about transformer with vision. Awesome Transformer with Computer Vision (CV)

Awesome Visual-Transformer Collect some Transformer with Computer-Vision (CV) papers. If you find some overlooked papers, please open issues or pull r

dkliang 2.8k Jan 08, 2023
JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation

JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation This the repository for this paper. Find extensions of this w

Zhuoyuan Mao 14 Oct 26, 2022
"Learning and Analyzing Generation Order for Undirected Sequence Models" in Findings of EMNLP, 2021

undirected-generation-dev This repo contains the source code of the models described in the following paper "Learning and Analyzing Generation Order f

Yichen Jiang 0 Mar 25, 2022
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

Apache MXNet (incubating) for Deep Learning Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to m

The Apache Software Foundation 20.2k Jan 05, 2023
[ICCV 2021 (oral)] Planar Surface Reconstruction from Sparse Views

Planar Surface Reconstruction From Sparse Views Linyi Jin, Shengyi Qian, Andrew Owens, David F. Fouhey University of Michigan ICCV 2021 (Oral) This re

Linyi Jin 89 Jan 05, 2023
Simple tools for logging and visualizing, loading and training

TNT TNT is a library providing powerful dataloading, logging and visualization utilities for Python. It is closely integrated with PyTorch and is desi

1.5k Jan 02, 2023
Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

StrengthNet Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis" https://arxiv.org/abs/2110

RuiLiu 65 Dec 20, 2022
Multiview 3D object detection on MultiviewC dataset through moft3d.

Multiview Orthographic Feature Transformation for 3D Object Detection Multiview 3D object detection on MultiviewC dataset through moft3d. Introduction

Jiahao Ma 20 Dec 21, 2022
Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"

SinGAN Project | Arxiv | CVF | Supplementary materials | Talk (ICCV`19) Official pytorch implementation of the paper: "SinGAN: Learning a Generative M

Tamar Rott Shaham 3.2k Dec 25, 2022
Implementation of the master's thesis "Temporal copying and local hallucination for video inpainting".

Temporal copying and local hallucination for video inpainting This repository contains the implementation of my master's thesis "Temporal copying and

David Álvarez de la Torre 1 Dec 02, 2022
A unified framework for machine learning with time series

Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible

The Alan Turing Institute 6k Jan 08, 2023
Code base for "On-the-Fly Test-time Adaptation for Medical Image Segmentation"

On-the-Fly Adaptation Official Pytorch Code base for On-the-Fly Test-time Adaptation for Medical Image Segmentation Paper Introduction One major probl

Jeya Maria Jose 17 Nov 10, 2022
Repository aimed at compiling code, papers, demos etc.. related to my PhD on 3D vision and machine learning for fruit detection and shape estimation at the university of Lincoln

PhD_3DPerception Repository aimed at compiling code, papers, demos etc.. related to my PhD on 3D vision and machine learning for fruit detection and s

lelouedec 2 Oct 06, 2022
Discover hidden deepweb pages

DeepWeb Scapper Att: Demo version An simple script to scrappe deepweb to find pages. Will return if any of those exists and will save on a file. You s

Héber Júlio 77 Oct 02, 2022
A foreign language learning aid using a neural network to predict probability of translating foreign words

Langy Langy is a reading-focused foreign language learning aid orientated towards young children. Reading is an activity that every child knows. It is

Shona Lowden 6 Nov 17, 2021