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Microbenchmarks in Big Data
M Microbenchmark Overview Microbenchmarks constitute the first line of per- Nicolas Poggi formance testing. Through them, we can ensure Databricks Inc., Amsterdam, NL, BarcelonaTech the proper and timely functioning of the different (UPC), Barcelona, Spain individual components that make up our system. The term micro, of course, depends on the prob- lem size. In BigData we broaden the concept Synonyms to cover the testing of large-scale distributed systems and computing frameworks. This chap- Component benchmark; Functional benchmark; ter presents the historical background, evolution, Test central ideas, and current key applications of the field concerning BigData. Definition Historical Background A microbenchmark is either a program or routine to measure and test the performance of a single Origins and CPU-Oriented Benchmarks component or task. Microbenchmarks are used to Microbenchmarks are closer to both hardware measure simple and well-defined quantities such and software testing than to competitive bench- as elapsed time, rate of operations, bandwidth, marking, opposed to application-level – macro or latency. Typically, microbenchmarks were as- – benchmarking. For this reason, we can trace sociated with the testing of individual software microbenchmarking influence to the hardware subroutines or lower-level hardware components testing discipline as can be found in Sumne such as the CPU and for a short period of time. (1974). Furthermore, we can also find influence However, in the BigData scope, the term mi- in the origins of software testing methodology crobenchmarking is broadened to include the during the 1970s, including works such cluster – group of networked computers – acting as Chow (1978). One of the first examples of as a single system, as well as the testing of a microbenchmark clearly distinguishable from frameworks, algorithms, logical and distributed software testing is the Whetstone benchmark components, for a longer period and larger data developed during the late 1960s and published sizes. -
Overview of the SPEC Benchmarks
9 Overview of the SPEC Benchmarks Kaivalya M. Dixit IBM Corporation “The reputation of current benchmarketing claims regarding system performance is on par with the promises made by politicians during elections.” Standard Performance Evaluation Corporation (SPEC) was founded in October, 1988, by Apollo, Hewlett-Packard,MIPS Computer Systems and SUN Microsystems in cooperation with E. E. Times. SPEC is a nonprofit consortium of 22 major computer vendors whose common goals are “to provide the industry with a realistic yardstick to measure the performance of advanced computer systems” and to educate consumers about the performance of vendors’ products. SPEC creates, maintains, distributes, and endorses a standardized set of application-oriented programs to be used as benchmarks. 489 490 CHAPTER 9 Overview of the SPEC Benchmarks 9.1 Historical Perspective Traditional benchmarks have failed to characterize the system performance of modern computer systems. Some of those benchmarks measure component-level performance, and some of the measurements are routinely published as system performance. Historically, vendors have characterized the performances of their systems in a variety of confusing metrics. In part, the confusion is due to a lack of credible performance information, agreement, and leadership among competing vendors. Many vendors characterize system performance in millions of instructions per second (MIPS) and millions of floating-point operations per second (MFLOPS). All instructions, however, are not equal. Since CISC machine instructions usually accomplish a lot more than those of RISC machines, comparing the instructions of a CISC machine and a RISC machine is similar to comparing Latin and Greek. 9.1.1 Simple CPU Benchmarks Truth in benchmarking is an oxymoron because vendors use benchmarks for marketing purposes. -
I.MX 8Quadxplus Power and Performance
NXP Semiconductors Document Number: AN12338 Application Note Rev. 4 , 04/2020 i.MX 8QuadXPlus Power and Performance 1. Introduction Contents This application note helps you to design power 1. Introduction ........................................................................ 1 management systems. It illustrates the current drain 2. Overview of i.MX 8QuadXPlus voltage supplies .............. 1 3. Power measurement of the i.MX 8QuadXPlus processor ... 2 measurements of the i.MX 8QuadXPlus Applications 3.1. VCC_SCU_1V8 power ........................................... 4 Processors taken on NXP Multisensory Evaluation Kit 3.2. VCC_DDRIO power ............................................... 4 (MEK) Platform through several use cases. 3.3. VCC_CPU/VCC_GPU/VCC_MAIN power ........... 5 3.4. Temperature measurements .................................... 5 This document provides details on the performance and 3.5. Hardware and software used ................................... 6 3.6. Measuring points on the MEK platform .................. 6 power consumption of the i.MX 8QuadXPlus 4. Use cases and measurement results .................................... 6 processors under a variety of low- and high-power 4.1. Low-power mode power consumption (Key States modes. or ‘KS’)…… ......................................................................... 7 4.2. Complex use case power consumption (Arm Core, The data presented in this application note is based on GPU active) ......................................................................... 11 5. SOC -
Part 1 of 4 : Introduction to RISC-V ISA
PULP PLATFORM Open Source Hardware, the way it should be! Working with RISC-V Part 1 of 4 : Introduction to RISC-V ISA Frank K. Gürkaynak <[email protected]> Luca Benini <[email protected]> http://pulp-platform.org @pulp_platform https://www.youtube.com/pulp_platform Working with RISC-V Summary ▪ Part 1 – Introduction to RISC-V ISA ▪ What is RISC-V about ▪ Description of ISA, and basic principles ▪ Simple 32b implementation (Ibex by LowRISC) ▪ How to extend the ISA (CV32E40P by OpenHW group) ▪ Part 2 – Advanced RISC-V Architectures ▪ Part 3 – PULP concepts ▪ Part 4 – PULP based chips | ACACES 2020 - July 2020 Working with RISC-V Few words about myself Frank K. Gürkaynak (just call me Frank) Senior scientist at ETH Zurich (means I am old) working with Luca Studied / Worked at Universities: in Turkey, United States and Switzerland (ETHZ and EPFL) Involved in Digital Design, Low Power Circuits, Open Source Hardware Part of PULP project from the beginning in 2013 | ACACES 2020 - July 2020 Working with RISC-V RISC-V Instruction Set Architecture ▪ Started by UC-Berkeley in 2010 SW ▪ Contract between SW and HW Applications ▪ Partitioned into user and privileged spec ▪ External Debug OS ▪ Standard governed by RISC-V foundation ▪ ETHZ is a founding member of the foundation ISA ▪ Necessary for the continuity User Privileged ▪ Defines 32, 64 and 128 bit ISA Debug ▪ No implementation, just the ISA ▪ Different implementations (both open and close source) HW ▪ At ETH Zurich we specialize in efficient implementations of RISC-V cores | ACACES 2020 - July 2020 Working with RISC-V RISC-V maintains basically a PDF document | ACACES 2020 - July 2020 Working with RISC-V ISA defines the instructions that processor uses C++ program translated to RISC-V instructions defined by ISA. -
Srovnání Kvality Virtuálních Strojů Assessment of Virtual Machines Performance
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by DSpace at VSB Technical University of Ostrava VŠB - Technická univerzita Ostrava Fakulta elektrotechniky a informatiky Katedra Informatiky Srovnání kvality virtuálních strojů Assessment of Virtual Machines Performance 2011 Lenka Novotná Prohlašuji, že jsem tuto bakalářskou práci vypracovala samostatně. Uvedla jsem všechny literární prameny a publikace, ze kterých jsem čerpala. V Ostravě dne 20. dubna 2011 ……………………… Lenka Novotná Ráda bych poděkovala vedoucímu bakalářské práce, Ing. Petru Olivkovi, za pomoc, věcné připomínky a veškerý čas, který mi věnoval. Abstrakt Hlavním cílem této bakalářské práce je vysvětlit pojem virtualizace, virtuální stroj, a dále popsat a porovnat dostupné virtualizační prostředky, které se využívají ve světovém oboru informačních technologií. Práce se především zabývá srovnáním výkonu virtualizačních strojů pro desktopové operační systémy MS Windows a Linux. Při testování jsem se zaměřila na tři hlavní faktory a to propustnost sítě, při které jsem použila aplikaci Iperf, ke změření výkonu diskových operací jsem využila program IOZone a pro test posledního faktoru, který je zaměřen na přidělování CPU procesů, jsem použila známé testovací aplikace Dhrystone a Whetstone. Všechna zmiňovaná měření okruhů byla provedena na třech virtualizačních platformách, kterými jsou VirtualBox OSE, VMware Player a KVM s QEMU. Klíčová slova: Virtualizace, virtuální stroj, VirtualBox, VMware, KVM, QEMU, plná virtualizace, paravirtualizace, částečná virtualizace, hardwarově asistovaná virtualizace, virtualizace na úrovní operačního systému, měření výkonu CPU, měření propustnosti sítě, měření diskových operací, Dhrystone, Whetstone, Iperf, IOZone. Abstract The main goal of this thesis is explain the term of Virtualization and Virtual Machine, describe and compare available virtualization resources, which we can use in worldwide field of information technology. -
Xilinx Running the Dhrystone 2.1 Benchmark on a Virtex-II Pro
Product Not Recommended for New Designs Application Note: Virtex-II Pro Device R Running the Dhrystone 2.1 Benchmark on a Virtex-II Pro PowerPC Processor XAPP507 (v1.0) July 11, 2005 Author: Paul Glover Summary This application note describes a working Virtex™-II Pro PowerPC™ system that uses the Dhrystone benchmark and the reference design on which the system runs. The Dhrystone benchmark is commonly used to measure CPU performance. Introduction The Dhrystone benchmark is a general-performance benchmark used to evaluate processor execution time. This benchmark tests the integer performance of a CPU and the optimization capabilities of the compiler used to generate the code. The output from the benchmark is the number of Dhrystones per second (that is, the number of iterations of the main code loop per second). This application note describes a PowerPC design created with Embedded Development Kit (EDK) 7.1 that runs the Dhrystone benchmark, producing 600+ DMIPS (Dhrystone Millions of Instructions Per Second) at 400 MHz. Prerequisites Required Software • Xilinx ISE 7.1i SP1 • Xilinx EDK 7.1i SP1 • WindRiver Diab DCC 5.2.1.0 or later Note: The Diab compiler for the PowerPC processor must be installed and included in the path. • HyperTerminal Required Hardware • Xilinx ML310 Demonstration Platform • Serial Cable • Xilinx Parallel-4 Configuration Cable Dhrystone Developed in 1984 by Reinhold P. Wecker, the Dhrystone benchmark (written in C) was Description originally developed to benchmark computer systems, a short benchmark that was representative of integer programming. The program is CPU-bound, performing no I/O functions or operating system calls. -
BOOM): an Industry- Competitive, Synthesizable, Parameterized RISC-V Processor
The Berkeley Out-of-Order Machine (BOOM): An Industry- Competitive, Synthesizable, Parameterized RISC-V Processor Christopher Celio David A. Patterson Krste Asanović Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2015-167 http://www.eecs.berkeley.edu/Pubs/TechRpts/2015/EECS-2015-167.html June 13, 2015 Copyright © 2015, by the author(s). All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. The Berkeley Out-of-Order Machine (BOOM): An Industry-Competitive, Synthesizable, Parameterized RISC-V Processor Christopher Celio, David Patterson, and Krste Asanovic´ University of California, Berkeley, California 94720–1770 [email protected] BOOM is a work-in-progress. Results shown are prelimi- nary and subject to change as of 2015 June. I$ L1 D$ (32k) L2 data 1. The Berkeley Out-of-Order Machine BOOM is a synthesizable, parameterized, superscalar out- exe of-order RISC-V core designed to serve as the prototypical baseline processor for future micro-architectural studies of uncore regfile out-of-order processors. Our goal is to provide a readable, issue open-source implementation for use in education, research, exe and industry. uncore BOOM is written in roughly 9,000 lines of the hardware L2 data (256k) construction language Chisel. -
Efficient Online Memory Error Assessment and Circumvention For
Int. J. Critical Computer-Based Systems, Vol. 4, No. 3, 227{247 1 Efficient Online Memory Error Assessment and Circumvention for Linux with RAMpage Horst Schirmeier*, Ingo Korb, Olaf Spinczyk and Michael Engel Department of Computer Science 12, Technische Universit¨atDortmund, Otto-Hahn-Str. 16, 44221 Dortmund, Germany E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] *Corresponding author Abstract: Memory errors are a major source of reliability problems in computer systems. Undetected errors may result in program termination or, even worse, silent data corruption. Recent studies have shown that the frequency of permanent memory errors is an order of magnitude higher than previously assumed and regularly affects everyday operation. To reduce the impact of memory errors, we designed RAMpage, a purely software-based infrastructure to assess and circumvent permanent memory errors in a running commodity x86-64 Linux-based system. We briefly describe the design and implementation of RAMpage and present new results from an extensive qualitative and quantitative evaluation. These results show the efficiency of our approach { RAMpage is able to provide a smooth graceful degradation in the presence of permanent memory errors while requiring only a small overhead in terms of CPU time, energy, and memory space. Keywords: Memory errors; Software-based fault tolerance; DRAM chips; Silent data corruption; Operating systems; Reliable operation Biographical notes: Horst Schirmeier received his Diploma in Computer Science from Friedrich-Alexander-Universit¨atErlangen, Germany. He worked as a researcher in the System Software group at FAU Erlangen, and is currently working in the field of resilient infrastructure software and fault resilience assessment for the DanceOS project in the Embedded System Software group at Technische Universit¨atDortmund, Germany. -
A Free, Commercially Representative Embedded Benchmark Suite
MiBench: A free, commercially representative embedded benchmark suite Matthew R. Guthaus, Jeffrey S. Ringenberg, Dan Ernst, Todd M. Austin, Trevor Mudge, Richard B. Brown {mguthaus,jringenb,ernstd,taustin,tnm,brown}@eecs.umich.edu The University of Michigan Electrical Engineering and Computer Science 1301 Beal Ave., Ann Arbor, MI 48109-2122 Abstract Among the common features of these This paper examines a set of commercially microarchitectures are deep pipelines, significant representative embedded programs and compares them instruction level parallelism, sophisticated branch to an existing benchmark suite, SPEC2000. A new prediction schemes, and large caches. version of SimpleScalar that has been adapted to the Although this class of machines has been the chief ARM instruction set is used to characterize the focus of the computer architecture community, performance of the benchmarks using configurations relatively few microprocessors are employed in this similar to current and next generation embedded market segment. The vast majority of microprocessors processors. Several characteristics distinguish the are employed in embedded applications [8]. Although representative embedded programs from the existing many are just inexpensive microcontrollers, their SPEC benchmarks including instruction distribution, combined sales account for nearly half of all memory behavior, and available parallelism. The microprocessor revenue. Furthermore, the embedded embedded benchmarks, called MiBench, are freely application domain is the fastest growing market available to all researchers. segment in the microprocessor industry. The wide range of applications makes it difficult to 1. Introduction characterize the embedded domain. In fact, an Performance based design has made benchmarking embedded benchmark suite should reflect this by a critical part of the design process [1]. -
An Evaluation of Soft Processors As a Reliable Computing Platform
Brigham Young University BYU ScholarsArchive Theses and Dissertations 2015-07-01 An Evaluation of Soft Processors as a Reliable Computing Platform Michael Robert Gardiner Brigham Young University - Provo Follow this and additional works at: https://scholarsarchive.byu.edu/etd Part of the Electrical and Computer Engineering Commons BYU ScholarsArchive Citation Gardiner, Michael Robert, "An Evaluation of Soft Processors as a Reliable Computing Platform" (2015). Theses and Dissertations. 5509. https://scholarsarchive.byu.edu/etd/5509 This Thesis is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of BYU ScholarsArchive. For more information, please contact [email protected], [email protected]. An Evaluation of Soft Processors as a Reliable Computing Platform Michael Robert Gardiner A thesis submitted to the faculty of Brigham Young University in partial fulfillment of the requirements for the degree of Master of Science Michael J. Wirthlin, Chair Brad L. Hutchings Brent E. Nelson Department of Electrical and Computer Engineering Brigham Young University July 2015 Copyright © 2015 Michael Robert Gardiner All Rights Reserved ABSTRACT An Evaluation of Soft Processors as a Reliable Computing Platform Michael Robert Gardiner Department of Electrical and Computer Engineering, BYU Master of Science This study evaluates the benefits and limitations of soft processors operating in a radiation-hardened FPGA, focusing primarily on the performance and reliability of these systems. FPGAs designs for four popular soft processors, the MicroBlaze, LEON3, Cortex- M0 DesignStart, and OpenRISC 1200 are developed for a Virtex-5 FPGA. The performance of these soft processor designs is then compared on ten widely-used benchmark programs. -
A 32-Bit Synthesizable Processor Core
IEIE Transactions on Smart Processing and Computing, vol. 4, no. 2, April 2015 http://dx.doi.org/10.5573/IEIESPC.2015.4.2.083 83 IEIE Transactions on Smart Processing and Computing Core-A: A 32-bit Synthesizable Processor Core Ji-Hoon Kim1,*, Jong-Yeol Lee2, and Ando Ki3 1 Department of Electronics Engineering, Chungnam National University / Daejeon, South Korea [email protected] 2 Division of Electronic Engineering, Chonbuk National University / Jeonju, South Korea [email protected] 3 R&D Center, Dynalith Systems / Daejeon, South Korea [email protected] * Corresponding Author: Ji-Hoon Kim Received November 20, 2014; Revised December 27, 2014; Accepted February 12, 2015; Published April 30, 2015 * Short Paper Review Paper: This paper reviews recent progress, possibly including previous works in a particular research topic, and has been accepted by the editorial board through the regular review process. Abstract: Core-A is 32-bit synthesizable processor core with a unique instruction set architecture (ISA). In this paper, the Core-A ISA is introduced with discussion of useful features and the development environment, including the software tool chain and hardware on-chip debugger. Core- A is described using Verilog-HDL and can be customized for a given application and synthesized for an application-specific integrated circuit or field-programmable gate array target. Also, the GNU Compiler Collection has been ported to support Core-A, and various predesigned platforms are well equipped with the established design flow to speed up the hardware/software co-design for a Core-A–based system. Keywords: Processor core, CPU, Embedded processor, Development environment 1. -
A Synthetic Benchmark
A synthetic benchmark H J Curnow and B A Wichmann Central Computer Agency, Riverwalk House, London SW1P 4RT National Physical Laboratory, Teddington, Middlesex TW11 OLW Computer Journal, Vol 19, No 1, pp43-49. 1976 Abstract A simple method of measuring performance is by means of a benchmark pro- gram. Unless such a program is carefully constructed it is unlikely to be typical of the many thousands of programs run at an installation. An example benchmark for measuring the processor power of scientific computers is presented: this is compared with other methods of assessing computer power. (Received December 1974) An important characteristic of computers used for scientific work is the speed of the central processor unit. A simple technique for comparing this speed for a variety of machines is to time some clearly defined task on each one. Unfortunately the ratio of speeds obtained varies enormously with the nature of the task being performed. If the task is defined informally in words, large variations can be caused by small differences in the tasks actually performed on the machines. These variations can be largely overcome by using a high level language to specify the task. An additional advantage of this method is that the efficiency of the compiler and the differences in machine architecture are automatically taken into account. In any case, most scientific programming is performed in high level languages, so these measurements will be a better guide to the machine’s capabilities than measurements based on use of low level languages. An example of the use of machine-independent languages to measure processing speed appears in Wichmann [7] which gives the times taken in microseconds to execute 42 basic statements in ALGOL 60 on some 50 machines.