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Using Dell EMC Unity Storage in an Equinix Cloud-Connected Data Center
Using Dell EMC Unity Storage in an Equinix Cloud- Connected Data Center A Detailed Review Abstract This whitepaper discusses use cases for running Dell EMC Unity storage in a public cloud colocation facility, validates storage latency and performance, and provides recommendations. October 2019 Dell EMC Technical White Paper Internal Use - Confidential Revisions Version Date Description 0.01 February 2019 Initial draft 0.18 May 2019 Updated to include Microsoft Azure 0.24 October 2019 Minor edits Acknowledgements This paper was produced by the following members of the Dell EMC Presales team: Author: Ryan Tassotti This whitepaper was possible thanks to the contributions from: • Rajiv Juneja Dell EMC • Alex Seymour Dell EMC • Gabriel Lageyre Equinix • Lee Sharping Equinix • Mischa Jampolsky Equinix The information in this publication is provided “as is.” Dell Inc. makes no representations or warranties of any kind with respect to the information in this publication, and specifically disclaims implied warranties of merchantability or fitness for a particular purpose. Use, copying, and distribution of any software described in this publication requires an applicable software license. © 2019 Dell Inc. or its subsidiaries. All Rights Reserved. Dell, EMC, Dell EMC and other trademarks are trademarks of Dell Inc. or its subsidiaries. Other trademarks may be trademarks of their respective owners. Equinix, Platform Equinix, and IBX are registered trademarks of Equinix, Inc. Equinix Cloud Exchange Fabric, ECX Fabric, and Equinix International Business Exchange are trademarks of Equinix, Inc. Dell believes the information in this document is accurate as of its publication date. The information is subject to change without notice. 2 Using Dell EMC Unity Storage in an Equinix Cloud-Connected Data Center Internal Use - Confidential Table of contents Revisions............................................................................................................................................................................ -
Starwind Virtual SAN ® Benchmarking Best Practices 1 One Stop Virtualization Shop
One Stop Virtualization Shop StarWind Virtual SAN® Benchmarking Best Practices FEBRUARY,2019 BEST PRACTICES StarWind Virtual SAN ® Benchmarking Best Practices 1 One Stop Virtualization Shop Trademarks “StarWind”, “StarWind Software” and the StarWind and the StarWind Software logos are registered trademarks of StarWind Software. “StarWind LSFS” is a trademark of StarWind Software which may be registered in some jurisdictions. All other trademarks are owned by their respective owners. Changes The material in this document is for information only and is subject to change without notice. While reasonable efforts have been made in the preparation of this document to assure its accuracy, StarWind Software assumes no liability resulting from errors or omissions in this document, or from the use of the information contained herein. StarWind Software reserves the right to make changes in the product design without reservation and without notification to its users. Technical Support and Services If you have questions about installing or using this software, check this and other documents first - you will find answers to most of your questions on the Technical Papers webpage or in StarWind Forum. If you need further assistance, please contact us . About StarWind StarWind is a pioneer in virtualization and a company that participated in the development of this technology from its earliest days. Now the company is among the leading vendors of software and hardware hyper-converged solutions. The company’s core product is the years-proven StarWind Virtual SAN, which allows SMB and ROBO to benefit from cost-efficient hyperconverged IT infrastructure. Having earned a reputation of reliability, StarWind created a hardware product line and is actively tapping into hyperconverged and storage appliances market. -
SQL Server Performance Tuning on Google Compute Engine
SQL Server Performance Tuning on Google Compute Engine Erik Darling Brent Ozar Unlimited March 2017 Table of contents Introduction Measuring your existing SQL Server Trending backup size Projecting future space requirements Trending backup speed Bonus section: Backing up to NUL Trending DBCC CHECKDB Trending index maintenance Recap: your current vital stats Sizing your Google Compute Engine VM Choosing your instance type Compute Engine’s relationship between cores and memory Memory is more important in the cloud Choosing your CPU type Putting it all together: build, then experiment Measuring what SQL Server is waiting on An introduction to wait stats Getting more granular wait stats data Wait type reference list CPU Memory Disk Locks Latches Misc Always On Availability Groups waits Demo: Showing wait stats with a live workload About the database: orders About the workload Measuring SQL Server with sp_BlitzFirst Baseline #1: Waiting on PAGEIOLATCH, CXPACKET, SOS_SCHEDULER_YIELD Mitigation #1: Fixing PAGEIOLATCH, SOS_SCHEDULER_YIELD Configuring SQL Server to use the increased power TempDB Moving TempDB Max server memory 1 CPU Baseline #2: PAGEIOLATCH gone, SOS_SCHEDULER_YIELD still here Mitigation #2: Adding cores for SOS_SCHEDULER_YIELD waits Baseline #3: High CPU, and now LCK* waits Mitigation #3: Fixing LCK* waits with optimistic isolation levels Batch requests per second 2 Introduction This whitepaper discusses how to create a SQL server in Compute Engine and then use performance metrics to optimize its performance. This paper is intended for database administrators, Windows admins, or developers planning to build your first SQL Servers in Google Compute Engine. In this white paper, you’ll learn how to do the following: ● Measure your current SQL Server using data already have. -
Electronics/Computers
Electronics/Computers Spaceborne Hybrid-FPGA System for Processing FTIR Data NASA’s Jet Propulsion Laboratory, Pasadena, California Progress has been made in a continu- vantage of the reconfigurable hardware in the software, it has been possible to re- ing effort to develop a spaceborne com- resources of the FPGAs. duce execution time to an eighth of that puter system for processing readout data The specific FPGA/embedded-proces- of a non-optimized software-only imple- from a Fourier-transform infrared sor combination selected for this effort is mentation. A concept for utilizing both (FTIR) spectrometer to reduce the vol- the Xilinx Virtex-4 FX hybrid FPGA with embedded PowerPC processors to fur- ume of data transmitted to Earth. The one of its two embedded IBM PowerPC ther reduce execution time has also been approach followed in this effort, ori- 405 processors. The effort has involved considered. ented toward reducing design time and exploration of various architectures and This work was done by Dmitriy L. Bekker, reducing the size and weight of the spec- hardware and software optimizations. By Jean-Francois L. Blavier, and Paula J. Pin- trometer electronics, has been to exploit including a dedicated floating-point unit gree of Caltech and Marcin Lukowiak and the versatility of recently developed hy- and a dot-product coprocessor in the Muhammad Shaaban of Rochester Institute brid field-programmable gate arrays hardware and utilizing optimized single- of Technology for NASA’s Jet Propulsion Lab- (FPGAs) to run diverse software on em- precision math library functions and a oratory. For more information, contact iaof- bedded processors while also taking ad- modified PowerPC performance library [email protected]. -
Contents Introduction
Contents Introduction ............................................................................................................................................. 2 General Performance Notes .................................................................................................................... 2 CB Protection Server One-tier Architecture .............................................................................................. 2 CB Protection Server Two-tier Architecture .............................................................................................. 3 Choosing Proper Hardware for the SQL Server .................................................................................... 3 Choosing Proper Hardware for CB Protection Server ........................................................................... 3 Network Configuration ......................................................................................................................... 3 Network Latency Impact....................................................................................................................... 3 SQL Permissions ..................................................................................................................................... 5 SQL Server Memory Configuration .......................................................................................................... 6 CB Protection Server Database Storage ................................................................................................. -
Seyyed Ahmad Javadi
Seyyed Ahmad Javadi <[email protected]> Address: Lab FE08, 15 JJ Thomson Avenue, Cambridge CB3 0FD http://www3.cs.stonybrook.edu/~sjavadi/ Phone number: +44-7936 875192 https://github.com/sajavadi RESEARCH INTERESTS • Cloud Computing, Distributed Systems, Performance Analysis and Modeling, Operating Systems EDUCATION PhD in Computer Science, Stony Brook University, USA Aug. 2014-Jun. 2019 • Advisor: Dr. Anshul Gandhi • Thesis title: Analytical Approaches for Dynamic Scheduling in Cloud Environments MSc in Software Engineering, Sharif University of Technology, Iran Sep. 2010-Sep. 2012 • Advisor: Prof. Rasool Jalili • Thesis title: Analysis of Non-monotonic Property in Access Control for Pervasive Computing Environments BSc in Software Engineering, Ferdowsi University of Mashhad, Iran Sep. 2006-Jul. 2010 TECHNICAL AND RESEARCH EXPERIENCE • Postdoctoral Researcher, University of Cambridge, CompAcctSys, July 2019-present – Current research: I am currently working on audit logging challenges in the Internet of Things, online social platforms, and cloud computing environments. The goal is to propose novel audit logging and distributed log analysis approaches that preserve users’ personal data privacy. These techniques can be leveraged to audit applications accessing users’ personal data at run-time and their access pattern as well as to detect malicious usages of online social platforms and machine learning as services, just to name a few. • Research Assistant, Stony Brook University, PACE Lab, January 2018-June 2019 – Resource-adaptive Batch Workload Management in Cloud Environments: Resource under-utilization is com- mon in cloud data centers. To improve server utilization, batch workloads can be run in the background to leverage idle resources. However, customer Virtual Machines’ (VMs) performance can be degraded because of resource con- tention. -
Of the Securities Exchange Act of 1934
FORM 8-K SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549 CURRENT REPORT Pursuant to Section 13 or 15(d) of the Securities Exchange Act of 1934 Date of Report: March 10, 1994 ADVANCED MICRO DEVICES, INC. ---------------------------------------------------- (Exact name of registrant as specified in its charter) Delaware 1-7882 94-1692300 - ------------------------------ ------------ ------------------- (State or other jurisdiction (Commission (I.R.S. Employer of incorporation) File Number) Identification No.) One AMD Place P.O. Box 3453 Sunnyvale, California 94088-3453 - --------------------------------------- ---------- (Address of principal executive office) (Zip Code) Registrant's telephone number, including area code: (408) 732-2400 Item 5 Other Events - ------ ------------ I. Litigation ---------- A. Intel ----- General ------- Advanced Micro Devices, Inc. ("AMD" or "Corporation") and Intel Corporation ("Intel") are engaged in a number of legal proceedings involving AMD's x86 products. The current status of such legal proceedings are described below. An unfavorable decision in the 287, 386 or 486 microcode cases could result in a material monetary award to Intel and/or preclude AMD from continuing to produce those Am386(Registered Trademark) and Am486(Trademark) products adjudicated to contain any copyrighted Intel microcode. The Am486 products are a material part of the Company's business and profits and such an unfavorable decision could have an immediate, materially adverse impact on the financial condition and results of the operations of AMD. The AMD/Intel legal proceedings involve multiple interrelated and complex issues of fact and law. The ultimate outcome of such legal proceedings cannot presently be determined. Accordingly, no provision for any liability that may result upon an adjudication of any of the AMD/Intel legal proceedings has been made in the Corporation's financial statements. -
2003 - 2019 Top 200 Employers for CPT Students**
2003 - 2019 Top 200 Employers for CPT Students** **If a student is employed at the same Employer while in a different program, he/she will be counted multiple times for that employer. Top 200 Employer Names Number of Students Participating in CPT in 2003-2019 Amazon 9,302 Intel Corporation 6,453 Microsoft Corporation 6,340 Google 6,132 IBM 4,721 Deloitte 3,870 Facebook 3,810 Qualcomm Technologies, Inc 3,371 Ernst & Young 2,929 Goldman Sachs 2,867 Cummins 2,729 JP Morgan Chase 2,474 PricewaterhouseCoopers 2,295 Bank of America 2,241 Apple, Inc 2,229 Cisco System, Inc 2,133 Disney 2,041 Morgan Stanley 1,970 World Bank 1,956 Citigroup 1,904 Merrill Lynch 1,850 KPMG 1,464 Dell, Inc 1,448 Yahoo 1,403 Motorola 1,357 Tesla, Inc 1,314 eBay or PayPal 1,268 Kelly Services 1,195 EMC Corporation 1,119 NVIDIA Corporation 1,110 Walmart 1,108 Samsung Research America 1,102 Ericsson, Inc 1,100 Adobe Systems Incorporated 1,085 PRO Unlimited 1,042 Texas Instruments 1,022 Credit Suisse 1017 Barclays 970 Randstad 942 Sony 930 Schlumberger 928 McKinsey & Company 883 2003 - 2019 Top 200 Employers for CPT Students** **If a student is employed at the same Employer while in a different program, he/she will be counted multiple times for that employer. VMWare 868 Adecco 845 Philips 829 Deutsche Bank 797 Broadcom Corporation 791 HP, Inc 789 Oracle 789 Advanced Micro Devices, Inc 782 Micron Technology, Inc 775 Boston Consulting Group 755 CVS Pharmacy 741 Robert Bosch LLC 723 Bloomberg 711 State Street 705 Hewlett-Packard 702 Alcatel-Lucent 666 Oak Ridge Institute for Science and Education 662 Genentech 657 Symantec Corporation 657 Nokia 642 Aerotek, Inc 638 Los Alamos National Laboratory 638 LinkedIn 635 Tekmark Global Solutions LLC 634 Populus Group 624 Salesforce 623 SAP America, Inc 619 Juniper Network 609 Atrium 584 The Mathworks, Inc 582 Monsanto 581 Wayfair 580 Autodesk 571 Intuit 562 Wells Fargo 559 Synopsys, Inc 546 NEC Laboratories America, Inc. -
3PAR Storeserv 8440 All-Flash Array and Store More Data in Less Space Thanks to Deduplication the Company Where Arthur Works Has a Fantastic Cafeteria
A Principled Technologies report: Hands-on testing. Real-world results. 30 times more IOPS Serve more users 01101001010 01011101001 01010010011 00100100111 96% lower latency Provide a better 01101001010 01011101001 01010010011 customer experience 00100100111 Data deduplication ratio of 11 to 1 Make the most of storage capacity compared to a legacy storage solution Improve database performance and response time with the HPE 3PAR StoreServ 8440 all-flash array and store more data in less space thanks to deduplication The company where Arthur works has a fantastic cafeteria. Lately, though, he’s been brown- bagging it and eating in his office to avoid running into database administrators. “You have to do something about the database servers!” they usually say, but he knows the problem is actually storage. While hard drive-based arrays once met the company’s needs, the data demands of employees and customers have exploded. Upgrading to speedier all-flash storage seems necessary, but Arthur is concerned about capacity. What his company needs is an SSD-based solution that can accommodate its current and future volumes of data. Could the HPE 3PAR StoreServ 8440 Storage array, which is powered by Intel® Xeon® processors, be what Arthur is looking for? In the Principled Technologies datacenter, we tested this all-flash storage solution, along with the older, hard drive-based HPE 3PAR StoreServ 7400 Storage array. We found that upgrading to the 8440 could dramatically improve both performance and response time and boost storage efficiency with inline deduplication. With results like that, Arthur could start eating in the cafeteria again! This report uses a fictional scenario in which a datacenter administrator considers upgrading to the all-flash HPE 3PAR StoreServ 8440 Storage array. -
ICE User Guide
ICE User Guide Document # 38-12005 Rev. *D Cypress Semiconductor 198 Champion Court San Jose, CA 95134-1709 Phone (USA): 800.858.1810 Phone (Intnl): 408.943.2600 http://www.cypress.com Copyrights Copyrights Copyright © 2005 Cypress Semiconductor Corporation. All rights reserved. “Programmable System-on-Chip,” PSoC, PSoC Designer, and PSoC Express are trademarks of Cypress Semiconductor Corporation (Cypress), along with Cypress® and Cypress Semiconductor™. All other trademarks or registered trademarks referenced herein are the property of their respective owners. The information in this document is subject to change without notice and should not be construed as a commitment by Cypress. While reasonable precautions have been taken, Cypress assumes no responsibility for any errors that may appear in this document. No part of this document may be copied or reproduced in any form or by any means without the prior written consent of Cypress. Made in the U.S.A. Disclaimer CYPRESS MAKES NO WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, WITH REGARD TO THIS MATERIAL, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PAR- TICULAR PURPOSE. Cypress reserves the right to make changes without further notice to the materials described herein. Cypress does not assume any liability arising out of the application or use of any product or circuit described herein. Cypress does not authorize its products for use as critical components in life-support systems where a malfunction or failure may rea- sonably be expected to result in significant injury to the user. The inclusion of Cypress’ product in a life-support systems appli- cation implies that the manufacturer assumes all risk of such use and in doing so indemnifies Cypress against all charges. -
The Diskspd Storage Performance Tool
The DiskSpd Storage Performance Tool DiskSpd is a highly customizable I/O load generator tool that can be used to run storage performance tests against files, partitions, or physical disks. DiskSpd can generate a wide variety of disk request patterns for use in analyzing and diagnosing storage performance issues, without running a full end-to- end workload. You can simulate SQL Server I/O activity or more complex, changing access patterns, returning detailed XML output for use in automated results analysis. Contents 1 Vision for the DiskSpd tool................................................................................................................... 3 1.1 Acknowledgments ...................................................................................................................... 3 2 The DiskSpd command and parameters ............................................................................................. 3 2.1 DiskSpd basic parameters ........................................................................................................... 3 2.2 DiskSpd event parameters .......................................................................................................... 7 2.3 ETW parameters for use with DiskSpd.exe................................................................................. 7 2.4 Size conventions for DiskSpd parameters .................................................................................. 8 3 Customizing DiskSpd tests .................................................................................................................. -
SQL Server Configuration Guide
BS SQL Server Configuration Guide Product Version: 8.6 Document Date: February, 2021 Copyright © 2004–2021 VMware, Inc. All rights reserved. This product may be covered under one or more patents pending. Carbon Black is a registered trademark and/or trademark of VMware, Inc. in the United States and other countries. All other trademarks and product names may be the trademarks of their respective owners. VMware, Inc. | 1100 Winter Street, Waltham, MA 02451 USA | Tel: 617.393.7400 Doc Revision 1.0 VMware Carbon Black App Control SQL Server Configuration Guide Contents Introduction ................................................................................................................................................... 3 General Performance Notes ......................................................................................................................... 3 App Control Server One-tier Architecture ..................................................................................................... 3 App Control Server Two-tier Architecture ..................................................................................................... 4 Choosing Proper Hardware for the SQL Server ....................................................................................... 4 Choosing Proper Hardware for App Control Server .................................................................................. 4 Network Configuration ..............................................................................................................................