Design and Analysis of a 32-Bit Embedded High-Performance Cluster Optimized for Energy and Performance – Extended Edition
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Shorten Device Boot Time for Automotive IVI and Navigation Systems
Shorten Device Boot Time for Automotive IVI and Navigation Systems Jim Huang ( 黃敬群 ) <[email protected]> Dr. Shi-wu Lo <[email protected]> May 28, 2013 / Automotive Linux Summit (Spring) Rights to copy © Copyright 2013 0xlab http://0xlab.org/ [email protected] Attribution – ShareAlike 3.0 Corrections, suggestions, contributions and translations You are free are welcome! to copy, distribute, display, and perform the work to make derivative works Latest update: May 28, 2013 to make commercial use of the work Under the following conditions Attribution. You must give the original author credit. Share Alike. If you alter, transform, or build upon this work, you may distribute the resulting work only under a license identical to this one. For any reuse or distribution, you must make clear to others the license terms of this work. Any of these conditions can be waived if you get permission from the copyright holder. Your fair use and other rights are in no way affected by the above. License text: http://creativecommons.org/licenses/by-sa/3.0/legalcode Goal of This Presentation • Propose a practical approach of the mixture of ARM hibernation (suspend to disk) and Linux user-space checkpointing – to shorten device boot time • An intrusive technique for Android/Linux – minimal init script and root file system changes are required • Boot time is one of the key factors for Automotive IVI – mentioned by “Linux Powered Clusters” and “Silver Bullet of Virtualization (Pitfalls, Challenges and Concerns) Continued” at ALS 2013 – highlighted by “Boot Time Optimizations” at ALS 2012 About this presentation • joint development efforts of the following entities – 0xlab team - http://0xlab.org/ – OSLab, National Chung Cheng University of Taiwan, led by Dr. -
Connecting Peripheral Devices to a Pandaboard Using
11/16/2012 MARK CONNECTING PERIPHERAL DEVICES TO A BIRDSALL PANDABOARD USING PSI This is an application note that will help somebody use the Serial Programming Interface that is available on the OMAP-based PandaBoard’s expansion connector and also explains how use the SPI to connect with a real-time clock (RTC) chip. Ever since the PandaBoard came out, there has been a community of eager programmers constructing creative projects and asking questions about where else and what more they could do to extend the PandaBoard’s abilities. This application note will document a way to connect devices to a OMAP-based devise like a PandaBoard What is the Serial Programming Interface “Serial Programming Interface” (SPI) is a simple standard that was developed my Motorola. SPI can also be called “4-wire” interface (as opposed to 1, 2 or 3-wire serial buses) and it is sometimes referred to like that because the interface has four wires defined. The first is Master- Out-Slave-In (MOSI) and the second is the Master-In-Slave-Out (MISO). There is also a Serial Clock from the Master (SCLK) and a Chipselect Signal (CS#) which can allow for more than one slave devise to be able to connect with one master. Why do we want to use the SPI? There are various ways to connect a peripheral device to the PandaBoard like USB, SPI, etc... and SPI has some advantages. Using the Serial Programming Interface costs less in terms of power usage and it is easy to connect different devises to the PandaBoard and also to debug any problems that occur all while maintaining an acceptable performance rate. -
Deliverable D4.1
Deliverable D4.1 – State of the art on performance and power estimation of embedded and high-performance cores Anastasiia Butko, Abdoulaye Gamatié, Gilles Sassatelli, Stefano Bernabovi, Michael Chapman, Philippe Naudin To cite this version: Anastasiia Butko, Abdoulaye Gamatié, Gilles Sassatelli, Stefano Bernabovi, Michael Chapman, et al.. Deliverable D4.1 – State of the art on performance and power estimation of embedded and high- performance cores. [Research Report] LIRMM (UM, CNRS); Cortus S.A.S. 2016. lirmm-03168326 HAL Id: lirmm-03168326 https://hal-lirmm.ccsd.cnrs.fr/lirmm-03168326 Submitted on 12 Mar 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Project Ref. Number ANR-15-CE25-0007 D4.1 – State of the art on performance and power estimation of embedded and high-performance cores Version 2.0 (2016) Final Public Distribution Main contributors: A. Butko, A. Gamatié, G. Sassatelli (LIRMM); S. Bernabovi, M. Chapman and P. Naudin (Cortus) Project Partners: Cortus S.A.S, Inria, LIRMM Every effort has been made to ensure that all statements and information contained herein are accurate, however the Continuum Project Partners accept no liability for any error or omission in the same. -
Setting up Odroid C2 – Throughtput Testing
Throughput Testing Single-Board Computer for Wireless LAN Professionals Setting up Odroid C2 As Test End-Point Inventory Project Items Unpack and knoll the following items ❑ Impact Strong 5200 mAh USB Battery o And it has a flashlight as well! ❑ USB Micro Power Cable (comes with Battery) ❑ Micro SD Card to eMCC adapter (Blueish green) ❑ eMCC Memory Card (small with Red label) ❑ Transcend USB 3.0 SD Card Reader ❑ Odroid Wi-Fi 4 NIC – (Black) ❑ USB ‘U-bend’ Adaper (Black ❑ Odroid C2 – Single Board Computer ❑ #WLPC_EU USB Drive (has the Image) ❑ Odroid Case Kit (Black) Later we will have you use as part of the testing (not in your own kit) • Small Phillips Screwdriver (to assemble your case) • Short Ethernet Cable (to test your unit when attached to a switch port) ❑ If you are running Windows copy the Win32DiskImager-0.9.5-binary executable as well. If you are running Windows follow the Windows directions, if Mac OS – move to the Mac OS directions. Mac OS Version Configure Image ❑ Copy Image File from the #WLPC_EU USB drive (in the Odroid for #WLPC_EU folder) to your Desktop… the file name is DietPi_v133_OdroidC2-arm64- (WLAN_PRO) ❑ Open Image File – Boot Drive ❑ Should have a Folder Call “Boot” ❑ Find the dietpi.txt We are changing setting so your Odroid device can join a local SSID and download more files we’ll need. ❑ Under the Wi-Fi Details section change the Wi-Fi SSID to WLPC_EU-01 with a PSK of password. #Enter your Wifi details below, if applicable (Case Sensitive). Wifi_SSID=WLPC_EU-01 Wifi_KEY=password ❑ Under WiFi Hotspot Settings, -
Cubietruck – Mini PC
SPRZĘT Cubietruck – mini PC Rynek komputerków jednopłytkowych opartych o procesory ARM zapoczątkowany przez Raspberry Pi rozwija się doskonale. Może nie jak grzyby po deszczu, ale systematycznie pojawiają się nowe rozwiązania: BeagleBoard, Marsboard, Cubieboard, Olinuxino itp. Różnią się one wyposażeniem, wydajnością, dostępnością dokumentacji oraz wsparciem technicznym. Ciekawie rozwija się propozycja Cubieboard. mocujących. Niby nic, ale te trzy kawałki two- org, zapoczątkowana płytką Cubieboard A10 rzywa i paczka tulejek umożliwiają poskładanie Fotografi a 3. Obudowa Cubietruck (opisaną w EP06/2013) i Cubieboard2 zgod- samodzielnego systemu mini-PC wyposażo- ną mechanicznie, ale zbudowaną w oparciu nego w dysk HDD 2,5”, wystarczająco zabez- rolę domowego centrum multimedialnego lub o nowszy, dwurdzeniowy procesor A20, zwięk- pieczając mechanicznie jego elementy. Osłony Linuxowego komputera PC. Jedyne zastrzeżenie szający wydajność Cubie i paletę jej zastosowań w odpowiednich miejscach mają wyfrezowane można mieć do kilku różnokolorowych LED, (fotografi a 1). Najnowsza propozycja to Cubie- otwory umożliwiające korzystanie z GPIO bez bezlitośnie informujących nasze oczy o stanie truck (Cubieboard3), oparty podobnie jak Cu- zdejmowania obudowy. pracy Cubie. bieboard2 (fotografi a 2) o procesor Allwinner Ciekawą propozycją dla osób wykorzy- Cubieboard3 oparty jest o SoC w architektu- A20, lecz mający znacznie bogatsze wyposaże- stujących Cubieboard3 w roli samodzielnego rze ARM7 – Allwinner A20, który w połączeniu nie, co niestety wiąże się z wyższą ceną. Porów- mini-PC, jest pełna obudowa pokazana na fo- ze sporej wielkości dyskiem NAND Flash oraz nanie parametrów poszczególnych komputer- tografi i 3. W swoim wnętrzu mieści swobodnie zwiększoną pamięcią RAM bezproblemowo ków Cubieboard umieszczono w tabeli 1. płytkę Cubieboard3, dysk HDD 2,5” (fotogra- sprawdza się w roli komputera PC pracującego Podobnie jak w przypadku poprzednich fi a 4) i przewody połączeniowe. -
Accelerating HPL Using the Intel Xeon Phi 7120P Coprocessors
Accelerating HPL using the Intel Xeon Phi 7120P Coprocessors Authors: Saeed Iqbal and Deepthi Cherlopalle The Intel Xeon Phi Series can be used to accelerate HPC applications in the C4130. The highly parallel architecture on Phi Coprocessors can boost the parallel applications. These coprocessors work seamlessly with the standard Xeon E5 processors series to provide additional parallel hardware to boost parallel applications. A key benefit of the Xeon Phi series is that these don’t require redesigning the application, only compiler directives are required to be able to use the Xeon Phi coprocessor. Fundamentally, the Intel Xeon series are many-core parallel processors, with each core having a dedicated L2 cache. The cores are connected through a bi-directional ring interconnects. Intel offers a complete set of development, performance monitoring and tuning tools through its Parallel Studio and VTune. The goal is to enable HPC users to get advantage from the parallel hardware with minimal changes to the code. The Xeon Phi has two modes of operation, the offload mode and native mode. In the offload mode designed parts of the application are “offloaded” to the Xeon Phi, if available in the server. Required code and data is copied from a host to the coprocessor, processing is done parallel in the Phi coprocessor and results move back to the host. There are two kinds of offload modes, non-shared and virtual-shared memory modes. Each offload mode offers different levels of user control on data movement to and from the coprocessor and incurs different types of overheads. In the native mode, the application runs on both host and Xeon Phi simultaneously, communication required data among themselves as need. -
Reverse Engineering Power Management on NVIDIA Gpus - Anatomy of an Autonomic-Ready System Martin Peres
Reverse Engineering Power Management on NVIDIA GPUs - Anatomy of an Autonomic-ready System Martin Peres To cite this version: Martin Peres. Reverse Engineering Power Management on NVIDIA GPUs - Anatomy of an Autonomic-ready System. ECRTS, Operating Systems Platforms for Embedded Real-Time appli- cations 2013, Jul 2013, Paris, France. hal-00853849 HAL Id: hal-00853849 https://hal.archives-ouvertes.fr/hal-00853849 Submitted on 23 Aug 2013 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Reverse engineering power management on NVIDIA GPUs - Anatomy of an autonomic-ready system Martin Peres Ph.D. student at LaBRI University of Bordeaux Hobbyist Linux/Nouveau Developer Email: [email protected] Abstract—Research in power management is currently limited supported nor documented by NVIDIA. As GPUs are leading by the fact that companies do not release enough documentation the market in terms of performance-per-Watt [3], they are or interfaces to fully exploit the potential found in modern a good candidate for a reverse engineering effort of their processors. This problem is even more present in GPUs despite power management features. The choice of reverse engineering having the highest performance-per-Watt ratio found in today’s NVIDIA’s power management features makes sense as they processors. -
A 2000 Frames / S Programmable Binary Image Processor Chip for Real Time Machine Vision Applications
A 2000 frames / s programmable binary image processor chip for real time machine vision applications A. Loos, D. Fey Institute of Computer Science, Friedrich-Schiller-University Jena Ernst-Abbe-Platz 2, D-07743 Jena, Germany {loos,fey}@cs.uni-jena.de Abstract the inflexible and fixed instruction set. To meet that we present a so called ASIP (application specific instruction Industrial manufacturing today requires both an efficient set processor) which combines the flexibility of a GPP production process and an appropriate quality standard of (General Purpose Processor) with the speed of an ASIC. each produced unit. The number of industrial vision appli- cations, where real time vision systems are utilized, is con- tinuously rising due to the increasing automation. Assem- Embedded Vision System bly lines, where component parts are manipulated by robot 1. real scene image sensing, AD- CMOS-Imager grippers, require a fast and fault tolerant visual detection conversion and read out of objects. Standard computation hardware like PC-based 2. grey scale image image segmentation platforms with frame grabber boards are often not appro- representation priate for such hard real time vision tasks in embedded sys- 3. raw binary image image enhancement, tems. This is because they meet their limits at frame rates of representation removal of disturbance a few hundreds images per second and show comparatively ASIP FPGA long latency times of a few milliseconds. This is the result 4. improved binary image calculation of of the largely serial working and time consuming process- projections ing chain of these systems. In contrast to that we designed 5. -
Intel Cirrascale and Petrobras Case Study
Case Study Intel® Xeon Phi™ Coprocessor Intel® Xeon® Processor E5 Family Big Data Analytics High-Performance Computing Energy Accelerating Energy Exploration with Intel® Xeon Phi™ Coprocessors Cirrascale delivers scalable performance by combining its innovative PCIe switch riser with Intel® processors and coprocessors To find new oil and gas reservoirs, organizations are focusing exploration in the deep sea and in complex geological formations. As energy companies such as Petrobras work to locate and map those reservoirs, they need powerful IT resources that can process multiple iterations of seismic models and quickly deliver precise results. IT solution provider Cirrascale began building systems with Intel® Xeon Phi™ coprocessors to provide the scalable performance Petrobras and other customers need while holding down costs. Challenges • Enable deep-sea exploration. Improve reservoir mapping accuracy with detailed seismic processing. • Accelerate performance of seismic applications. Speed time to results while controlling costs. • Improve scalability. Enable server performance and density to scale as data volumes grow and workloads become more demanding. Solution • Custom Cirrascale servers with Intel Xeon Phi coprocessors. Employ new compute blades with the Intel® Xeon® processor E5 family and Intel Xeon Phi coprocessors. Cirrascale uses custom PCIe switch risers for fast, peer-to-peer communication among coprocessors. Technology Results • Linear scaling. Performance increases linearly as Intel Xeon Phi coprocessors “Working together, the are added to the system. Intel® Xeon® processors • Simplified development model. Developers no longer need to spend time optimizing data placement. and Intel® Xeon Phi™ coprocessors help Business Value • Faster, better analysis. More detailed and accurate modeling in less time HPC applications shed improves oil and gas exploration. -
United Health Group Capacity Analysis
Advanced Technical Skills (ATS) North America zPCR Capacity Sizing Lab SHARE Sessions 7774 and 7785 August 4, 2010 John Burg Brad Snyder Materials created by John Fitch and Jim Shaw IBM 1 © 2010 IBM Corporation Advanced Technical Skills Trademarks The following are trademarks of the International Business Machines Corporation in the United States and/or other countries. AlphaBlox* GDPS* RACF* Tivoli* APPN* HiperSockets Redbooks* Tivoli Storage Manager CICS* HyperSwap Resource Link TotalStorage* CICS/VSE* IBM* RETAIN* VSE/ESA Cool Blue IBM eServer REXX VTAM* DB2* IBM logo* RMF WebSphere* DFSMS IMS S/390* xSeries* DFSMShsm Language Environment* Scalable Architecture for Financial Reporting z9* DFSMSrmm Lotus* Sysplex Timer* z10 DirMaint Large System Performance Reference™ (LSPR™) Systems Director Active Energy Manager z10 BC DRDA* Multiprise* System/370 z10 EC DS6000 MVS System p* z/Architecture* DS8000 OMEGAMON* System Storage zEnterprise ECKD Parallel Sysplex* System x* z/OS* ESCON* Performance Toolkit for VM System z z/VM* FICON* PowerPC* System z9* z/VSE FlashCopy* PR/SM System z10 zSeries* * Registered trademarks of IBM Corporation Processor Resource/Systems Manager The following are trademarks or registered trademarks of other companies. Adobe, the Adobe logo, PostScript, and the PostScript logo are either registered trademarks or trademarks of Adobe Systems Incorporated in the United States, and/or other countries. Cell Broadband Engine is a trademark of Sony Computer Entertainment, Inc. in the United States, other countries, or both and is used under license therefrom. Java and all Java-based trademarks are trademarks of Sun Microsystems, Inc. in the United States, other countries, or both. Microsoft, Windows, Windows NT, and the Windows logo are trademarks of Microsoft Corporation in the United States, other countries, or both. -
Improving the Beaglebone Board with Embedded Ubuntu, Enhanced GPMC Driver and Python for Communication and Graphical Prototypes
Final Master Thesis Improving the BeagleBone board with embedded Ubuntu, enhanced GPMC driver and Python for communication and graphical prototypes By RUBÉN GONZÁLEZ MUÑOZ Directed by MANUEL M. DOMINGUEZ PUMAR FINAL MASTER THESIS 30 ECTS, JULY 2015, ELECTRICAL AND ELECTRONICS ENGINEERING Abstract Abstract BeagleBone is a low price, small size Linux embedded microcomputer with a full set of I/O pins and processing power for real-time applications, also expandable with cape pluggable boards. The current work has been focused on improving the performance of this board. In this case, the BeagleBone comes with a pre-installed Angstrom OS and with a cape board using a particular software “overlay” and applications. Due to a lack of support, this pre-installed OS has been replaced by Ubuntu. As a consequence, the cape software and applications need to be adapted. Another necessity that emerges from the stated changes is to improve the communications through a GPMC interface. The depicted driver has been built for the new system as well as synchronous variants, also developed and tested. Finally, a set of applications in Python using the cape functionalities has been developed. Some extra graphical features have been included as example. Contents Contents Abstract ..................................................................................................................................................................................... 5 List of figures ......................................................................................................................................................................... -
The Von Neumann Computer Model 5/30/17, 10:03 PM
The von Neumann Computer Model 5/30/17, 10:03 PM CIS-77 Home http://www.c-jump.com/CIS77/CIS77syllabus.htm The von Neumann Computer Model 1. The von Neumann Computer Model 2. Components of the Von Neumann Model 3. Communication Between Memory and Processing Unit 4. CPU data-path 5. Memory Operations 6. Understanding the MAR and the MDR 7. Understanding the MAR and the MDR, Cont. 8. ALU, the Processing Unit 9. ALU and the Word Length 10. Control Unit 11. Control Unit, Cont. 12. Input/Output 13. Input/Output Ports 14. Input/Output Address Space 15. Console Input/Output in Protected Memory Mode 16. Instruction Processing 17. Instruction Components 18. Why Learn Intel x86 ISA ? 19. Design of the x86 CPU Instruction Set 20. CPU Instruction Set 21. History of IBM PC 22. Early x86 Processor Family 23. 8086 and 8088 CPU 24. 80186 CPU 25. 80286 CPU 26. 80386 CPU 27. 80386 CPU, Cont. 28. 80486 CPU 29. Pentium (Intel 80586) 30. Pentium Pro 31. Pentium II 32. Itanium processor 1. The von Neumann Computer Model Von Neumann computer systems contain three main building blocks: The following block diagram shows major relationship between CPU components: the central processing unit (CPU), memory, and input/output devices (I/O). These three components are connected together using the system bus. The most prominent items within the CPU are the registers: they can be manipulated directly by a computer program. http://www.c-jump.com/CIS77/CPU/VonNeumann/lecture.html Page 1 of 15 IPR2017-01532 FanDuel, et al.