Intel® Parallel Studio Xe 2017 Runtime
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Using Intel® Math Kernel Library and Intel® Integrated Performance Primitives in the Microsoft* .NET* Framework
Using Intel® MKL and Intel® IPP in Microsoft* .NET* Framework Using Intel® Math Kernel Library and Intel® Integrated Performance Primitives in the Microsoft* .NET* Framework Document Number: 323195-001US.pdf 1 Using Intel® MKL and Intel® IPP in Microsoft* .NET* Framework INFORMATION IN THIS DOCUMENT IS PROVIDED IN CONNECTION WITH INTEL® PRODUCTS. NO LICENSE, EXPRESS OR IMPLIED, BY ESTOPPEL OR OTHERWISE, TO ANY INTELLECTUAL PROPERTY RIGHTS IS GRANTED BY THIS DOCUMENT. EXCEPT AS PROVIDED IN INTEL'S TERMS AND CONDITIONS OF SALE FOR SUCH PRODUCTS, INTEL ASSUMES NO LIABILITY WHATSOEVER, AND INTEL DISCLAIMS ANY EXPRESS OR IMPLIED WARRANTY, RELATING TO SALE AND/OR USE OF INTEL PRODUCTS INCLUDING LIABILITY OR WARRANTIES RELATING TO FITNESS FOR A PARTICULAR PURPOSE, MERCHANTABILITY, OR INFRINGEMENT OF ANY PATENT, COPYRIGHT OR OTHER INTELLECTUAL PROPERTY RIGHT. UNLESS OTHERWISE AGREED IN WRITING BY INTEL, THE INTEL PRODUCTS ARE NOT DESIGNED NOR INTENDED FOR ANY APPLICATION IN WHICH THE FAILURE OF THE INTEL PRODUCT COULD CREATE A SITUATION WHERE PERSONAL INJURY OR DEATH MAY OCCUR. Intel may make changes to specifications and product descriptions at any time, without notice. Designers must not rely on the absence or characteristics of any features or instructions marked "reserved" or "undefined." Intel reserves these for future definition and shall have no responsibility whatsoever for conflicts or incompatibilities arising from future changes to them. The information here is subject to change without notice. Do not finalize a design with this information. The products described in this document may contain design defects or errors known as errata which may cause the product to deviate from published specifications. -
Intel® Parallel Studio
Intel® Parallel Studio Product Brief Parallelism for Your Development Lifecycle Intel® Parallel Studio Intel® Parallel Studio brings comprehensive parallelism to C/C++ Microsoft Visual Studio* application development. Parallel Studio was created in direct response to the concerns of software industry leaders and developers. From the way the products work together to support the development lifecycle to their unique feature sets, parallelism is now easier and more viable than ever before. The tools are designed so those new to parallelism can learn as they go, and experienced parallel programmers can work more efficiently and with more confidence. Parallel Studio is interoperable with common parallel programming libraries and API standards, such as Intel® Threading Building Blocks (Intel® TBB) and OpenMP*, and provides an immediate opportunity to realize the benefits of multicore platforms. “Intel® Parallel Studio makes the new Envivio 4Caster Series Transcoder’s development faster and more efficient. The tools included in Intel Parallel Studio, such as Intel® Parallel Inspector, Intel® Parallel Amplifier, and Intel® Parallel Composer (which consists of the Intel® C++ Compiler, Intel® IPP, and Intel® TBB) shortens our overall software development time by increasing the code’s reliability and its performance in a multicore multithreaded environment. At the qualification stage, the number of dysfunctions is reduced due to a safer implementation, and the bug tracking becomes easier too. Intel Parallel Studio globally speeds up our software products’ time-to-market”. Eric Rosier V.P. Engineering Envivio Intel® Parallel Studio Tools c. How can you actually boost performance of your threaded application on multicore processors and make the performance scale with additional cores? Intel® Parallel Studio Workflow The workflow diagram below depicts a typical usage model across all Intel Parallel Studio Addresses the Issues Listed Above. -
Michael Steyer Technical Consulting Engineer Intel Architecture, Graphics & Software Analysis Tools
Michael Steyer Technical Consulting Engineer Intel Architecture, Graphics & Software Analysis Tools Optimization Notice Copyright © 2020, Intel Corporation. All rights reserved. *Other names and brands may be claimed as the property of others. Aspects of HPC/Throughput Application Performance What are the Aspects of Performance Intel Hardware Features Multi-core Intel® Omni Intel® Optane™ Intel® Advanced Intel® Path HBM DC persistent Vector Xeon® Extensions 512 Architecture memory (Intel® AVX-512) processor Distributed memory Memory I/O Threading CPU Core Message size False Sharing File I/O Threaded/serial ratio uArch issues (IPC) Rank placement Access with strides I/O latency Thread Imbalance Vectorization Rank Imbalance Latency I/O waits RTL overhead FPU usage efficiency RTL Overhead Bandwidth System-wide I/O (scheduling, forking) Network Bandwidth NUMA Synchronization Cluster Node Core Optimization Notice Copyright © 2020, Intel Corporation. All rights reserved. *Other names and brands may be claimed as the property of others. IntelWhat Parallel are the Studio Aspects Tools covering of Performance the Aspects Intel Hardware Features Multi-core Intel® Intel® Omni Intel® Optane™ Advanced Intel®Path DC persistent Intel® Vector HBM Extensions Architectur Intel® VTune™memory AmplifierXeon® processor 512 (Intel® Tracee Intel®AVX-512) DistributedAnalyzer memory Memory I/O Threading AdvisorCPU Core Messageand size False Sharing File I/O Threaded/serial ratio uArch issues (IPC) Rank placement Access with strides I/O latency Thread Imbalance Vectorization RankCollector Imbalance Latency I/O waits RTL overhead FPU usage efficiency RTL Overhead Bandwidth System-wide I/O (scheduling, forking) Network Bandwidth NUMA Synchronization Cluster Node Core Optimization Notice Copyright © 2020, Intel Corporation. All rights reserved. -
Accelerate AI, HPC, Enterprise & Cloud Applications
Accelerate AI, HPC, Enterprise & Cloud Applications April 2019 @ CiTIUS: Centro Singular de Investigación en Tecnoloxías da Información Intel Computing Performance and Software Products (CPDP) Edmund Preiss Agenda • Intel Software Development Tools • Intel optimized AI Solutions Optimization Notice Copyright © 2018, Intel Corporation. All rights reserved. 3 *Other names and brands may be claimed as the property of others. Intel® Software Developer Tools & SDKs Intel® Parallel Studio XE Intel® System Studio Comprehensive Enterprise , HPC Embedded Tools Suite Tools suite Comprehensive, all-in-one, cross-platform Shared and distributed memory system & IoT development tool suite systems Simplifies system bring-up, boosts Code creation and versatile SW performance and power efficiency, Analysis Tools strengthens system reliability Intel® Media Server Studio OpenVINO™ Media Encode/Decode Tools Machine Learning / Deep Learning Inference Media SDK Computer Vision SDK Graphics Perf Analyzer Deep Learning (DL) Deployment Toolkit Computer Vision SDK Deep Learning Algorithms Open CL SDK Optimized DL Frameworks Context SDK Optimization Notice Copyright © 2018, Intel Corporation. All rights reserved. INTEL CONFIDENTIAL 11 *Other names and brands may be claimed as the property of others. What’s Inside Intel® Parallel Studio XE Comprehensive Software Development Tool Suite Cluster Edition Composer Edition Professional Edition BUILD ANALYZE SCALE Compilers & Libraries Analysis Tools Cluster Tools C / C++ Compiler Intel® Math Kernel Library Intel® VTune™ -
Intel® Software Products Highlights and Best Practices
Intel® Software Products Highlights and Best Practices Edmund Preiss Business Development Manager Entdecken Sie weitere interessante Artikel und News zum Thema auf all-electronics.de! Hier klicken & informieren! Agenda • Key enhancements and highlights since ISTEP’11 • Industry segments using Intel® Software Development Products • Customer Demo and Best Practices Copyright© 2012, Intel Corporation. All rights reserved. 2 *Other brands and names are the property of their respective owners. Key enhancements & highlights since ISTEP’11 3 All in One -- Intel® Cluster Studio XE 2012 Analysis & Correctness Tools Shared & Distributed Memory Application Development Intel Cluster Studio XE supports: -Shared Memory Processing MPI Libraries & Tools -Distributed Memory Processing Compilers & Libraries Programming Models -Hybrid Processing Copyright© 2012, Intel Corporation. All rights reserved. *Other brands and names are the property of their respective owners. Intel® VTune™ Amplifier XE New VTune Amplifier XE features very well received by Software Developers Key reasons : • More intuitive – Improved GUI points to application inefficiencies • Preconfigured & customizable analysis profiles • Timeline View highlights concurrency issues • New Event/PC counter ratio analysis concept easy to grasp Copyright© 2012, Intel Corporation. All rights reserved. *Other brands and names are the property of their respective owners. Intel® VTune™ Amplifier XE The Old Way versus The New Way The Old Way: To see if there is an issue with branch misprediction, multiply event value (86,400,000) by 14 cycles, then divide by CPU_CLK_UNHALTED.THREAD (5,214,000,000). Then compare the resulting value to a threshold. If it is too high, investigate. The New Way: Look at the Branch Mispredict metric, and see if any cells are pink. -
Intel(R) Math Kernel Library for Linux* OS User's Guide
Intel® Math Kernel Library for Linux* OS User's Guide MKL 10.3 - Linux* OS Document Number: 315930-012US Legal Information Legal Information INFORMATION IN THIS DOCUMENT IS PROVIDED IN CONNECTION WITH INTEL(R) PRODUCTS. NO LICENSE, EXPRESS OR IMPLIED, BY ESTOPPEL OR OTHERWISE, TO ANY INTELLECTUAL PROPERTY RIGHTS IS GRANTED BY THIS DOCUMENT. EXCEPT AS PROVIDED IN INTEL'S TERMS AND CONDITIONS OF SALE FOR SUCH PRODUCTS, INTEL ASSUMES NO LIABILITY WHATSOEVER, AND INTEL DISCLAIMS ANY EXPRESS OR IMPLIED WARRANTY, RELATING TO SALE AND/OR USE OF INTEL PRODUCTS INCLUDING LIABILITY OR WARRANTIES RELATING TO FITNESS FOR A PARTICULAR PURPOSE, MERCHANTABILITY, OR INFRINGEMENT OF ANY PATENT, COPYRIGHT OR OTHER INTELLECTUAL PROPERTY RIGHT. UNLESS OTHERWISE AGREED IN WRITING BY INTEL, THE INTEL PRODUCTS ARE NOT DESIGNED NOR INTENDED FOR ANY APPLICATION IN WHICH THE FAILURE OF THE INTEL PRODUCT COULD CREATE A SITUATION WHERE PERSONAL INJURY OR DEATH MAY OCCUR. Intel may make changes to specifications and product descriptions at any time, without notice. Designers must not rely on the absence or characteristics of any features or instructions marked "reserved" or "undefined." Intel reserves these for future definition and shall have no responsibility whatsoever for conflicts or incompatibilities arising from future changes to them. The information here is subject to change without notice. Do not finalize a design with this information. The products described in this document may contain design defects or errors known as errata which may cause the product to deviate from published specifications. Current characterized errata are available on request. Contact your local Intel sales office or your distributor to obtain the latest specifications and before placing your product order. -
Intel® Math Kernel Library for Windows* OS User's Guide
Intel® Math Kernel Library for Windows* OS User's Guide Intel® MKL - Windows* OS Document Number: 315930-027US Legal Information Contents Contents Legal Information................................................................................7 Introducing the Intel® Math Kernel Library...........................................9 Getting Help and Support...................................................................11 Notational Conventions......................................................................13 Chapter 1: Overview Document Overview.................................................................................15 What's New.............................................................................................15 Related Information.................................................................................15 Chapter 2: Getting Started Checking Your Installation.........................................................................17 Setting Environment Variables ..................................................................17 Compiler Support.....................................................................................19 Using Code Examples...............................................................................19 What You Need to Know Before You Begin Using the Intel® Math Kernel Library...............................................................................................19 Chapter 3: Structure of the Intel® Math Kernel Library Architecture Support................................................................................23 -
0 BLIS: a Modern Alternative to the BLAS
0 BLIS: A Modern Alternative to the BLAS FIELD G. VAN ZEE and ROBERT A. VAN DE GEIJN, The University of Texas at Austin We propose the portable BLAS-like Interface Software (BLIS) framework which addresses a number of short- comings in both the original BLAS interface and present-day BLAS implementations. The framework allows developers to rapidly instantiate high-performance BLAS-like libraries on existing and new architectures with relatively little effort. The key to this achievement is the observation that virtually all computation within level-2 and level-3 BLAS operations may be expressed in terms of very simple kernels. Higher-level framework code is generalized so that it can be reused and/or re-parameterized for different operations (as well as different architectures) with little to no modification. Inserting high-performance kernels into the framework facilitates the immediate optimization of any and all BLAS-like operations which are cast in terms of these kernels, and thus the framework acts as a productivity multiplier. Users of BLAS-dependent applications are supported through a straightforward compatibility layer, though calling sequences must be updated for those who wish to access new functionality. Experimental performance of level-2 and level-3 operations is observed to be competitive with two mature open source libraries (OpenBLAS and ATLAS) as well as an established commercial product (Intel MKL). Categories and Subject Descriptors: G.4 [Mathematical Software]: Efficiency General Terms: Algorithms, Performance Additional Key Words and Phrases: linear algebra, libraries, high-performance, matrix, BLAS ACM Reference Format: ACM Trans. Math. Softw. 0, 0, Article 0 ( 0000), 31 pages. -
5. Oneapi in Der Praxis
Praxis Gekonntes Zusammenspiel von HPC und AI im Alltag der Software-Entwickler oneAPI in der Praxis von Harald Odendahl Aus Parallel Studio XE wird oneAPI Toolkit: Software-Entwickler können ab Dezember 2020 auf die neue Generation der Programmier-Tools von Intel zugreifen. Die klassischen Intel-Tools sowie der professionelle Kunden-Support bleiben erhalten. Der Praxiseinsatz wird jedoch mächtig erweitert. Mit oneAPI bekräftigt Intel seinen Umschwung zu einer „Software First“-Strategie, um die Herausforderungen und Bedürfnisse der Programmierer bei der Entwicklung hochperformanter wissenschaftlicher und technischer Applikationen sowie KI-Anwendungen zu priorisieren. Das Design neuer Architekturen und Komponenten wie CPUs oder GPUs soll nun gleichzeitig und im Einklang mit den Innovationen bei Programmiermodellen und Entwicklertools erfolgen. So kündigte Intel auf der (virtuellen) Konferenz SuperComputing 2020 an, dass das von Native-Code-Entwicklern geschätzte und intensiv genutzte Intel Parallel Studio XE Toolkit ab Anfang 2021 von den neuen Toolkits der Produktfamilie oneAPI abgelöst werden wird. Intel will auf diesem Weg auch seinen Entwicklerkreis erweitern und bietet deshalb eine Reihe separater Toolkits für verschiedene Anwendungsgebiete. Historisch gesehen sind die klassischen Intel-Entwicklertools die Compiler für C/C++ sowie Fortran, die Analyse-Tools für Code- Optimierung sowie die bestbewährten Bibliotheken, wie zum Beispiel MKL oder IPP. Alle Komponenten werden in den neuen Toolkits vollständig übernommen. Die Leistungen für professionelle Nutzer, wie direkter Support von Intel-Ingenieuren und die Softwarewartung, bleiben bei weitgehend gleicher Preisstruktur erhalten. Erweiterte Tool-Palette für neue Nutzerkreise Im Packaging wird es jedoch eine Reihe von Änderungen geben. Zunächst führt Intel ein sogenanntes „oneAPI Base Toolkit“ ein, das einerseits die wesentlichen Komponenten für die architekturübergreifende Entwicklung zur Verfügung stellt und andererseits als Grundlage für weitere Toolkits dient. -
0 BLIS: a Framework for Rapidly Instantiating BLAS Functionality
0 BLIS: A Framework for Rapidly Instantiating BLAS Functionality FIELD G. VAN ZEE and ROBERT A. VAN DE GEIJN, The University of Texas at Austin The BLAS-like Library Instantiation Software (BLIS) framework is a new infrastructure for rapidly in- stantiating Basic Linear Algebra Subprograms (BLAS) functionality. Its fundamental innovation is that virtually all computation within level-2 (matrix-vector) and level-3 (matrix-matrix) BLAS operations can be expressed and optimized in terms of very simple kernels. While others have had similar insights, BLIS reduces the necessary kernels to what we believe is the simplest set that still supports the high performance that the computational science community demands. Higher-level framework code is generalized and imple- mented in ISO C99 so that it can be reused and/or re-parameterized for different operations (and different architectures) with little to no modification. Inserting high-performance kernels into the framework facili- tates the immediate optimization of any BLAS-like operations which are cast in terms of these kernels, and thus the framework acts as a productivity multiplier. Users of BLAS-dependent applications are given a choice of using the the traditional Fortran-77 BLAS interface, a generalized C interface, or any other higher level interface that builds upon this latter API. Preliminary performance of level-2 and level-3 operations is observed to be competitive with two mature open source libraries (OpenBLAS and ATLAS) as well as an established commercial product (Intel MKL). Categories and Subject Descriptors: G.4 [Mathematical Software]: Efficiency General Terms: Algorithms, Performance Additional Key Words and Phrases: linear algebra, libraries, high-performance, matrix, BLAS ACM Reference Format: ACM Trans. -
Accelerating Spark ML Applications Date Published: 2020-01-16 Date Modified
Best Practices Accelerating Spark ML Applications Date published: 2020-01-16 Date modified: https://docs.cloudera.com/ Legal Notice © Cloudera Inc. 2021. All rights reserved. The documentation is and contains Cloudera proprietary information protected by copyright and other intellectual property rights. No license under copyright or any other intellectual property right is granted herein. Copyright information for Cloudera software may be found within the documentation accompanying each component in a particular release. Cloudera software includes software from various open source or other third party projects, and may be released under the Apache Software License 2.0 (“ASLv2”), the Affero General Public License version 3 (AGPLv3), or other license terms. Other software included may be released under the terms of alternative open source licenses. Please review the license and notice files accompanying the software for additional licensing information. Please visit the Cloudera software product page for more information on Cloudera software. For more information on Cloudera support services, please visit either the Support or Sales page. Feel free to contact us directly to discuss your specific needs. Cloudera reserves the right to change any products at any time, and without notice. Cloudera assumes no responsibility nor liability arising from the use of products, except as expressly agreed to in writing by Cloudera. Cloudera, Cloudera Altus, HUE, Impala, Cloudera Impala, and other Cloudera marks are registered or unregistered trademarks in the United States and other countries. All other trademarks are the property of their respective owners. Disclaimer: EXCEPT AS EXPRESSLY PROVIDED IN A WRITTEN AGREEMENT WITH CLOUDERA, CLOUDERA DOES NOT MAKE NOR GIVE ANY REPRESENTATION, WARRANTY, NOR COVENANT OF ANY KIND, WHETHER EXPRESS OR IMPLIED, IN CONNECTION WITH CLOUDERA TECHNOLOGY OR RELATED SUPPORT PROVIDED IN CONNECTION THEREWITH. -
Intel Threading Building Blocks
Praise for Intel Threading Building Blocks “The Age of Serial Computing is over. With the advent of multi-core processors, parallel- computing technology that was once relegated to universities and research labs is now emerging as mainstream. Intel Threading Building Blocks updates and greatly expands the ‘work-stealing’ technology pioneered by the MIT Cilk system of 15 years ago, providing a modern industrial-strength C++ library for concurrent programming. “Not only does this book offer an excellent introduction to the library, it furnishes novices and experts alike with a clear and accessible discussion of the complexities of concurrency.” — Charles E. Leiserson, MIT Computer Science and Artificial Intelligence Laboratory “We used to say make it right, then make it fast. We can’t do that anymore. TBB lets us design for correctness and speed up front for Maya. This book shows you how to extract the most benefit from using TBB in your code.” — Martin Watt, Senior Software Engineer, Autodesk “TBB promises to change how parallel programming is done in C++. This book will be extremely useful to any C++ programmer. With this book, James achieves two important goals: • Presents an excellent introduction to parallel programming, illustrating the most com- mon parallel programming patterns and the forces governing their use. • Documents the Threading Building Blocks C++ library—a library that provides generic algorithms for these patterns. “TBB incorporates many of the best ideas that researchers in object-oriented parallel computing developed in the last two decades.” — Marc Snir, Head of the Computer Science Department, University of Illinois at Urbana-Champaign “This book was my first introduction to Intel Threading Building Blocks.