Computer Architecture

•Transferir como PPT, PDF•

1 gostou•506 visualizações

Sonal Patil

Computer Architecture Applications of Computer Architecture

Applications of CA ,[object Object],[object Object]

Engineering Design and Automation ,[object Object]

Engineering Design and Automation ,[object Object],[object Object]

Energy resources explorations ,[object Object]

Energy resources explorations ,[object Object],[object Object],[object Object],[object Object]

Mais conteúdo relacionado

Mais procurados

TIGER/Line Data in the Cloud - Tom MacWright

CrisisCommons

TIGER/line Data and Open Data in the Cloud

tmcw

solar air heater Using ANN

RAJBALA PURNIMA PRIYA

My topic of thesis is about constructing prediction model of wind energy and solar energy by artificial neural network with genetic algorithm. Because the electricity price in Nordic area is determined in advance, it is beneficial to construct prediction model for renewable energy. With the mentioned prediction model, we can construct hybrid system (wind energy and solar energy) to produce hydrogen. Then the fuel cell can produce electricity and connect to the network by using the constructed prediction model. In our prediction model, the critical parameters like 10 minutes average wind speed and deviation for wind energy could be used as historical data to train to artificial neural network (ANN). We also hope to utilize genetic algorithm (GA) to speed up the ANN training and hybrid system scale design.

FORECASTING OF RENEWABLE ENERGY PRODUCTION BY USING GENETIC ALGORITHM (GA) FO...

u772020

Tianjin Case Study

VisionMap

Session 2, part 2: What OCRE is Offering? Urban climate requirements. Nektari...

OCRE | Open Clouds for Research Environments

Simulation-Based Engineering for Satellite Applications

Ansys

Approach: -Starting with Made-in-Europe mature software stack, and optimizing this stack to support energy-efficiency -Integrated software stack supporting task-based programming model -Computing on a commercial cutting-edge European-developed CPU–GPU–FPGA heterogeneous hardware substrate and FPGA-based Dataflow Engines (DFE) -Three use-cases (Smart home/city, AI, health) to test the integrated stack

HiPEAC 2020: Energy-aware Task Scheduling in LEGaTO: Low Energy Toolset for H...

LEGATO project

mohamed nasr

Hassan - Condor _48_x_36

Hassan Tavakol-davani

Big Data Analytics for Satellite Image Processing and Remote Sensing (Advance...

xoneveh

What is GIS 2

Christopher Ball

In this video from GTC 2018, Peter Dueben from ECMWF presents: How to Prepare Weather and Climate Models for Future HPC Hardware. "Learn how one of the leading institutes for global weather predictions, the European Centre for Medium-Range Weather Forecasts (ECMWF), is preparing for exascale supercomputing and the efficient use of future HPC computing hardware. I will name the main reasons why it is difficult to design efficient weather and climate models and provide an overview on the ongoing community effort to achieve the best possible model performance on existing and future HPC architectures. I will present the EU H2020 projects ESCAPE and ESiWACE and discuss recent approaches to increase computing performance in weather and climate modeling such as the use of reduced numerical precision and deep learning." Watch the video: https://wp.me/p3RLHQ-ixu Learn more: https://www.ecmwf.int/ and https://www.nvidia.com/en-us/gtc/ Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter

How to Prepare Weather and Climate Models for Future HPC Hardware

inside-BigData.com

Computational fluid dynamics (CFD) can serve as a complementary approach to conventional wind tunnel testing to assess the wind flow around tall buildings. Being a clear high-Performance Computing (HPC) task, CFD simulations conventionally run on supercomputers and compute clusters using specialized software such as OpenFOAM. The limited availability and high maintenance costs of supercomputers and clusters force small and medium companies to search for the cost-efficient infrastructure to conduct their simulations with the appropriate performance. The on-demand offer of computing capacity by cloud service providers are well suited to this task. However, engineers and researchers require extensive expertise and experience in working with cloud computing in order to benefit from running CFD simulations on a cloud.

Windsurfing with APPA: Automating the Computational Fluid Dynamics Simulation...

Anshul Jindal

The success of the Cloud computing paradigm, together with the increase of Cloud providers and optimized Infrastructure-as-a-Service (IaaS) offerings have contributed to a raise in the number of research and industry communities that are strong supporters of migrating and running their applications in the Cloud. Focusing on eScience simulation-based applications, scientific workflows have been widely adopted in the last years, and the scientific workflow management systems have become strong candidates for being migrated to the Cloud. In this research work we aim at empirically evaluating multiple Cloud providers and their corresponding optimized and non-optimized IaaS offerings with respect to their offered performance, and its impact on the incurred monetary costs when migrating and executing a workflow-based simulation environment. The experiments show significant performance improvements and reduced monetary costs when executing the simulation environment in off-premise Clouds.

Performance_and_Cost_Evaluation

Santiago Gómez Sáez

Feature Selection and Optimization of Artificial Neural Network for Short Ter...

Maged M. ElJazzar

Copernicus hackathon

Antonis Vatousios

Electrical load forecasting using Hijri causal events

Maged M. ElJazzar

AI Artificial Intelligence. Landslide velocity prediction applied to the Cass...

Claudio Angelino

Oral presentation1

rockinggirl

Mais procurados (20)

TIGER/Line Data in the Cloud - Tom MacWright

TIGER/line Data and Open Data in the Cloud

solar air heater Using ANN

FORECASTING OF RENEWABLE ENERGY PRODUCTION BY USING GENETIC ALGORITHM (GA) FO...

Tianjin Case Study

Session 2, part 2: What OCRE is Offering? Urban climate requirements. Nektari...

Simulation-Based Engineering for Satellite Applications

HiPEAC 2020: Energy-aware Task Scheduling in LEGaTO: Low Energy Toolset for H...

Hassan - Condor _48_x_36

Big Data Analytics for Satellite Image Processing and Remote Sensing (Advance...

What is GIS 2

How to Prepare Weather and Climate Models for Future HPC Hardware

Windsurfing with APPA: Automating the Computational Fluid Dynamics Simulation...

Performance_and_Cost_Evaluation

Feature Selection and Optimization of Artificial Neural Network for Short Ter...

Copernicus hackathon

Electrical load forecasting using Hijri causal events

AI Artificial Intelligence. Landslide velocity prediction applied to the Cass...

Oral presentation1

Semelhante a Computer Architecture

Intelligent Energy Systems

Thorsten MAYER

Omniverse for the Metaverse

Alison B. Lowndes

applications-and-current-challenges-of-supercomputing-across-multiple-domains...

Neha Gupta

AIAA Future of Fluids 2018 Boris

Qiqi Wang

How to leverage Quantum Computing and Generative AI for Clean Energy Transiti...

Sayonsom Chanda

Digital Infrastructure in a Carbon-Constrained World

Larry Smarr

QUANTUM COMPUTING APPLICATION.pptx

NehaFatima30

Applications of PARALLEL PROCESSING

Praveen Kumar

Agents In An Exponential World Foster

Ian Foster

Super Computer

Zeeshan Rana

Cluster Tutorial

cybercbm

Supercomputer

Systronic IT Group PTY LTD

Most experts would consider this the biggest challenge. Quantum computers are extremely sensitive to noise and errors caused by interactions with their environment. This can cause errors to accumulate and degrade the quality of computation. Developing reliable error correction techniques is therefore essential for building practical quantum computers. While quantum computers have shown impressive performance for some tasks, they are still relatively small compared to classical computers. Scaling up quantum computers to hundreds or thousands of qubits while maintaining high levels of coherence and low error rates remains a major challenge. Developing high-quality quantum hardware, such as qubits and control electronics, is a major challenge. There are many different qubit technologies, each with its own strengths and weaknesses, and developing a scalable, fault-tolerant qubit technology is a major focus of research. Funding agencies, such as government agencies, are rising to the occasion to invest in tackling these quantum computing challenges. Researchers — almost daily — are making advances in the engineering and scientific challenges to create practical quantum computers

Call for Chapters- Edited Book: Real World Challenges in Quantum Electronics ...

Christo Ananth

B Kindilien-Does Manufacturing Have a Future?

Summary

General Resume

Future of hpc

In this deck from DataTech19, Debbie Bard from NERSC presents: Supercomputing and the scientist: How HPC and large-scale data analytics are transforming experimental science. "Debbie Bard leads the Data Science Engagement Group NERSC. NERSC is the mission supercomputing center for the USA Department of Energy, and supports over 7000 scientists and 700 projects with supercomputing needs. A native of the UK, her career spans research in particle physics, cosmology and computing on both sides of the Atlantic. She obtained her PhD at Edinburgh University, and has worked at Imperial College London as well as the Stanford Linear Accelerator Center (SLAC) in the USA, before joining the Data Department at NERSC, where she focuses on data-intensive computing and research, including supercomputing for experimental science and machine learning at scale." Watch the video: https://wp.me/p3RLHQ-kLV Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter

How HPC and large-scale data analytics are transforming experimental science

inside-BigData.com

r1501e

George Vamos

The Academic and R&D Sectors' Current and Future Broadband and Fiber Access N...

Larry Smarr

Semelhante a Computer Architecture (20)

Intelligent Energy Systems

Omniverse for the Metaverse

applications-and-current-challenges-of-supercomputing-across-multiple-domains...

AIAA Future of Fluids 2018 Boris

How to leverage Quantum Computing and Generative AI for Clean Energy Transiti...

Digital Infrastructure in a Carbon-Constrained World

QUANTUM COMPUTING APPLICATION.pptx

Applications of PARALLEL PROCESSING

Agents In An Exponential World Foster

Super Computer

Cluster Tutorial

Supercomputer

Call for Chapters- Edited Book: Real World Challenges in Quantum Electronics ...

B Kindilien-Does Manufacturing Have a Future?

Summary

General Resume

Future of hpc

How HPC and large-scale data analytics are transforming experimental science

r1501e

The Academic and R&D Sectors' Current and Future Broadband and Fiber Access N...

Mais de Sonal Patil

GWT_Framework

Sonal Patil

Wireless Microserver

Sonal Patil

The Key To Anger Reduction Is Knowing Yourself

Sonal Patil

Satrack

Sonal Patil

Millipede Memory

Sonal Patil

Internet Access Via Cable Network

Gift

Frndship

Frnd

Brain Computer Interface

Best Photos

A Wise Camel

Anand Sagar

Air Powered Car

11ways

R U Hungry

Attitude

10 Words

The Bank Account Of Life

Sonal Patil

Mais de Sonal Patil (19)

GWT_Framework

Wireless Microserver

The Key To Anger Reduction Is Knowing Yourself

Satrack

Millipede Memory

Internet Access Via Cable Network

Gift

Frndship

Frnd

Brain Computer Interface

Best Photos

A Wise Camel

Anand Sagar

Air Powered Car

11ways

R U Hungry

Attitude

10 Words

The Bank Account Of Life