Hardware Acceleration
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Field Programmable Gate Arrays with Hardwired Networks on Chip
Field Programmable Gate Arrays with Hardwired Networks on Chip PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Technische Universiteit Delft, op gezag van de Rector Magnificus prof. ir. K.C.A.M. Luyben, voorzitter van het College voor Promoties, in het openbaar te verdedigen op dinsdag 6 november 2012 om 15:00 uur door MUHAMMAD AQEEL WAHLAH Master of Science in Information Technology Pakistan Institute of Engineering and Applied Sciences (PIEAS) geboren te Lahore, Pakistan. Dit proefschrift is goedgekeurd door de promotor: Prof. dr. K.G.W. Goossens Copromotor: Dr. ir. J.S.S.M. Wong Samenstelling promotiecommissie: Rector Magnificus voorzitter Prof. dr. K.G.W. Goossens Technische Universiteit Eindhoven, promotor Dr. ir. J.S.S.M. Wong Technische Universiteit Delft, copromotor Prof. dr. S. Pillement Technical University of Nantes, France Prof. dr.-Ing. M. Hubner Ruhr-Universitat-Bochum, Germany Prof. dr. D. Stroobandt University of Gent, Belgium Prof. dr. K.L.M. Bertels Technische Universiteit Delft Prof. dr.ir. A.J. van der Veen Technische Universiteit Delft, reservelid ISBN: 978-94-6186-066-8 Keywords: Field Programmable Gate Arrays, Hardwired, Networks on Chip Copyright ⃝c 2012 Muhammad Aqeel Wahlah All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without permission of the author. Printed in The Netherlands Acknowledgments oday when I look back, I find it a very interesting journey filled with different emotions, i.e., joy and frustration, hope and despair, and T laughter and sadness. -
NASDAQ Stock Market
Nasdaq Stock Market Friday, December 28, 2018 Name Symbol Close 1st Constitution Bancorp FCCY 19.75 1st Source SRCE 40.25 2U TWOU 48.31 21st Century Fox Cl A FOXA 47.97 21st Century Fox Cl B FOX 47.62 21Vianet Group ADR VNET 8.63 51job ADR JOBS 61.7 111 ADR YI 6.05 360 Finance ADR QFIN 15.74 1347 Property Insurance Holdings PIH 4.05 1-800-FLOWERS.COM Cl A FLWS 11.92 AAON AAON 34.85 Abiomed ABMD 318.17 Acacia Communications ACIA 37.69 Acacia Research - Acacia ACTG 3 Technologies Acadia Healthcare ACHC 25.56 ACADIA Pharmaceuticals ACAD 15.65 Acceleron Pharma XLRN 44.13 Access National ANCX 21.31 Accuray ARAY 3.45 AcelRx Pharmaceuticals ACRX 2.34 Aceto ACET 0.82 Achaogen AKAO 1.31 Achillion Pharmaceuticals ACHN 1.48 AC Immune ACIU 9.78 ACI Worldwide ACIW 27.25 Aclaris Therapeutics ACRS 7.31 ACM Research Cl A ACMR 10.47 Acorda Therapeutics ACOR 14.98 Activision Blizzard ATVI 46.8 Adamas Pharmaceuticals ADMS 8.45 Adaptimmune Therapeutics ADR ADAP 5.15 Addus HomeCare ADUS 67.27 ADDvantage Technologies Group AEY 1.43 Adobe ADBE 223.13 Adtran ADTN 10.82 Aduro Biotech ADRO 2.65 Advanced Emissions Solutions ADES 10.07 Advanced Energy Industries AEIS 42.71 Advanced Micro Devices AMD 17.82 Advaxis ADXS 0.19 Adverum Biotechnologies ADVM 3.2 Aegion AEGN 16.24 Aeglea BioTherapeutics AGLE 7.67 Aemetis AMTX 0.57 Aerie Pharmaceuticals AERI 35.52 AeroVironment AVAV 67.57 Aevi Genomic Medicine GNMX 0.67 Affimed AFMD 3.11 Agile Therapeutics AGRX 0.61 Agilysys AGYS 14.59 Agios Pharmaceuticals AGIO 45.3 AGNC Investment AGNC 17.73 AgroFresh Solutions AGFS 3.85 -
IBIS Open Forum Minutes
IBIS Open Forum Minutes Meeting Date: March 12, 2010 Meeting Location: Teleconference VOTING MEMBERS AND 2010 PARTICIPANTS Actel (Prabhu Mohan) Agilent Radek Biernacki, Ming Yan, Fangyi Rao AMD Nam Nguyen Ansoft Corporation (Steve Pytel) Apple Computer (Matt Herndon) Applied Simulation Technology (Fred Balistreri) ARM (Nirav Patel) Cadence Design Systems Terry Jernberg*, Wenliang Dai, Ambrish Varma Cisco Systems Syed Huq*, Mike LaBonte*, Tony Penaloza, Huyen Pham, Bill Chen, Ravindra Gali, Zhiping Yang Ericsson Anders Ekholm*, Pete Tomaszewski Freescale Jon Burnett, Om Mandhana Green Streak Programs Lynne Green Hitachi ULSI Systems (Kazuyoshi Shoji) Huawei Technologies (Jinjun Li) IBM Adge Hawes* Infineon Technologies AG (Christian Sporrer) Intel Corporation (Michael Mirmak), Myoung (Joon) Choi, Vishram Pandit, Richard Mellitz IO Methodology Lance Wang* LSI Brian Burdick* Mentor Graphics Arpad Muranyi*, Neil Fernandes, Zhen Mu Micron Technology Randy Wolff* Nokia Siemens Networks GmbH Eckhard Lenski* Samtec (Corey Kimble) Signal Integrity Software Walter Katz*, Mike Steinberger, Todd Westerhoff, Barry Katz Sigrity Brad Brim, Kumar Keshavan Synopsys Ted Mido Teraspeed Consulting Group Bob Ross*, Tom Dagostino Toshiba (Yasumasa Kondo) Xilinx Mike Jenkins ZTE (Huang Min) Zuken Michael Schaeder OTHER PARTICIPANTS IN 2010 AET, Inc. Mikio Kiyono Altera John Oh, Hui Fu Avago Razi Kaw Broadcom Mohammad Ali Curtiss-Wright John Phillips ECL, Inc. Tom Iddings eSilicon Hanza Rahmai Exar Corp. Helen Nguyen Mindspeed Bobby Altaf National Semiconductor Hsinho Wu* NetLogic Microsystems Eric Hsu, Edward Wu Renesas Technology Takuji Komeda Simberian Yuriy Shlepnev Span Systems Corporation Vidya (Viddy) Amirapu Summit Computer Systems Bob Davis Tabula David Banas* TechAmerica (Chris Denham) Texas Instruments Bonnie Baker Independent AbdulRahman (Abbey) Rafiq, Robert Badal In the list above, attendees at the meeting are indicated by *. -
Enabling Hardware Accelerated Video Decode on Intel® Atom™ Processor D2000 and N2000 Series Under Fedora 16
Enabling Hardware Accelerated Video Decode on Intel® Atom™ Processor D2000 and N2000 Series under Fedora 16 Application Note October 2012 Order Number: 509577-003US INFORMATIONLegal Lines and Disclaimers 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. A “Mission Critical Application” is any application in which failure of the Intel Product could result, directly or indirectly, in personal injury or death. SHOULD YOU PURCHASE OR USE INTEL'S PRODUCTS FOR ANY SUCH MISSION CRITICAL APPLICATION, YOU SHALL INDEMNIFY AND HOLD INTEL AND ITS SUBSIDIARIES, SUBCONTRACTORS AND AFFILIATES, AND THE DIRECTORS, OFFICERS, AND EMPLOYEES OF EACH, HARMLESS AGAINST ALL CLAIMS COSTS, DAMAGES, AND EXPENSES AND REASONABLE ATTORNEYS' FEES ARISING OUT OF, DIRECTLY OR INDIRECTLY, ANY CLAIM OF PRODUCT LIABILITY, PERSONAL INJURY, OR DEATH ARISING IN ANY WAY OUT OF SUCH MISSION CRITICAL APPLICATION, WHETHER OR NOT INTEL OR ITS SUBCONTRACTOR WAS NEGLIGENT IN THE DESIGN, MANUFACTURE, OR WARNING OF THE INTEL PRODUCT OR ANY OF ITS PARTS. 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”. -
Moore's Law Motivation
Motivation: Moore’s Law • Every two years: – Double the number of transistors CprE 488 – Embedded Systems Design – Build higher performance general-purpose processors Lecture 8 – Hardware Acceleration • Make the transistors available to the masses • Increase performance (1.8×↑) Joseph Zambreno • Lower the cost of computing (1.8×↓) Electrical and Computer Engineering Iowa State University • Sounds great, what’s the catch? www.ece.iastate.edu/~zambreno rcl.ece.iastate.edu Gordon Moore First, solve the problem. Then, write the code. – John Johnson Zambreno, Spring 2017 © ISU CprE 488 (Hardware Acceleration) Lect-08.2 Motivation: Moore’s Law (cont.) Motivation: Dennard Scaling • The “catch” – powering the transistors without • As transistors get smaller their power density stays melting the chip! constant 10,000,000,000 2,200,000,000 Transistor: 2D Voltage-Controlled Switch 1,000,000,000 Chip Transistor Dimensions 100,000,000 Count Voltage 10,000,000 ×0.7 1,000,000 Doping Concentrations 100,000 Robert Dennard 10,000 2300 Area 0.5×↓ 1,000 130W 100 Capacitance 0.7×↓ 10 0.5W 1 Frequency 1.4×↑ 0 Power = Capacitance × Frequency × Voltage2 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Power 0.5×↓ Zambreno, Spring 2017 © ISU CprE 488 (Hardware Acceleration) Lect-08.3 Zambreno, Spring 2017 © ISU CprE 488 (Hardware Acceleration) Lect-08.4 Motivation Dennard Scaling (cont.) Motivation: Dark Silicon • In mid 2000s, Dennard scaling “broke” • Dark silicon – the fraction of transistors that need to be powered off at all times (due to power + thermal -
Use of Hardware Acceleration on PC As of March, 2020
Use of hardware acceleration on PC As of March, 2020 When displaying images of the camera using hardware acceleration of the PC, required the specifications of PC as folow. "The PC is equipped with specific hardware (CPU*1, GPU, etc.), and device drivers corresponding to those hardware are installed properly." ® *1: The CPU of the PC must support QSV(Intel Quick Sync Video). This information provides test results conducted under our environment and does not guarantee under all conditions. Please note that we used Internet Explorer for downloading at the following description and its procedures may differ if you use another browser software. Images may not be displayed, may be delayed or some of the images may be corrupted as follow, depends on usage conditions, performance and network environment of the PC. - When multiple windows are opened and operated on the PC - When sufficient bandwidth cannot be secured in your network environment - When the network driver of your computer is old (the latest version is recommended) *When the image is not displayed or the image is distorted, it may be improved by refreshing the browser. Applicable models: i-PRO EXTREME series models*2 (H.265/H.264 compatible models and H.265 compatible models) , i-PRO SmartHD series models*2 (H.264 compatible models) *2: You can find if it supports hardware acceleration by existence a setting item of [Drawing method] and [Decoding Options] in [Viewer software (nwcv4Ssetup.exe/ nwcv5Ssetup.exe)] of the setting menu of the camera. Items of the function that utilize PC hardware acceleration (Click the items as follow to go to each setting procedures.) 1.About checking if it supports "QSV" 2. -
NVIDIA Ampere GA102 GPU Architecture Whitepaper
NVIDIA AMPERE GA102 GPU ARCHITECTURE Second-Generation RTX Updated with NVIDIA RTX A6000 and NVIDIA A40 Information V2.0 Table of Contents Introduction 5 GA102 Key Features 7 2x FP32 Processing 7 Second-Generation RT Core 7 Third-Generation Tensor Cores 8 GDDR6X and GDDR6 Memory 8 Third-Generation NVLink® 8 PCIe Gen 4 9 Ampere GPU Architecture In-Depth 10 GPC, TPC, and SM High-Level Architecture 10 ROP Optimizations 11 GA10x SM Architecture 11 2x FP32 Throughput 12 Larger and Faster Unified Shared Memory and L1 Data Cache 13 Performance Per Watt 16 Second-Generation Ray Tracing Engine in GA10x GPUs 17 Ampere Architecture RTX Processors in Action 19 GA10x GPU Hardware Acceleration for Ray-Traced Motion Blur 20 Third-Generation Tensor Cores in GA10x GPUs 24 Comparison of Turing vs GA10x GPU Tensor Cores 24 NVIDIA Ampere Architecture Tensor Cores Support New DL Data Types 26 Fine-Grained Structured Sparsity 26 NVIDIA DLSS 8K 28 GDDR6X Memory 30 RTX IO 32 Introducing NVIDIA RTX IO 33 How NVIDIA RTX IO Works 34 Display and Video Engine 38 DisplayPort 1.4a with DSC 1.2a 38 HDMI 2.1 with DSC 1.2a 38 Fifth Generation NVDEC - Hardware-Accelerated Video Decoding 39 AV1 Hardware Decode 40 Seventh Generation NVENC - Hardware-Accelerated Video Encoding 40 NVIDIA Ampere GA102 GPU Architecture ii Conclusion 42 Appendix A - Additional GeForce GA10x GPU Specifications 44 GeForce RTX 3090 44 GeForce RTX 3070 46 Appendix B - New Memory Error Detection and Replay (EDR) Technology 49 Appendix C - RTX A6000 GPU Perf ormance 50 List of Figures Figure 1. -
Research Into Computer Hardware Acceleration of Data Reduction and SVMS
University of Rhode Island DigitalCommons@URI Open Access Dissertations 2016 Research Into Computer Hardware Acceleration of Data Reduction and SVMS Jason Kane University of Rhode Island, [email protected] Follow this and additional works at: https://digitalcommons.uri.edu/oa_diss Recommended Citation Kane, Jason, "Research Into Computer Hardware Acceleration of Data Reduction and SVMS" (2016). Open Access Dissertations. Paper 428. https://digitalcommons.uri.edu/oa_diss/428 This Dissertation is brought to you for free and open access by DigitalCommons@URI. It has been accepted for inclusion in Open Access Dissertations by an authorized administrator of DigitalCommons@URI. For more information, please contact [email protected]. RESEARCH INTO COMPUTER HARDWARE ACCELERATION OF DATA REDUCTION AND SVMS BY JASON KANE A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN COMPUTER ENGINEERING UNIVERSITY OF RHODE ISLAND 2016 DOCTOR OF PHILOSOPHY DISSERTATION OF JASON KANE APPROVED: Dissertation Committee: Major Professor Qing Yang Haibo He Joan Peckham Nasser H. Zawia DEAN OF THE GRADUATE SCHOOL UNIVERSITY OF RHODE ISLAND 2016 ABSTRACT Yearly increases in computer performance have diminished as of late, mostly due to the inability of transistors, the building blocks of computers, to deliver the same rate of performance seen in the 1980’s and 90’s. Shifting away from traditional CPU design, accelerator architectures have been shown to offer a potentially untapped solution. These architectures implement unique, custom hardware to increase the speed of certain tasking, such as graphics processing. The studies undertaken for this dissertation examine the ability of unique accelerator hardware to provide improved power and speed performance over traditional means, with an emphasis on classification tasking. -
Review of FPD's Languages, Compilers, Interpreters and Tools
ISSN 2394-7314 International Journal of Novel Research in Computer Science and Software Engineering Vol. 3, Issue 1, pp: (140-158), Month: January-April 2016, Available at: www.noveltyjournals.com Review of FPD'S Languages, Compilers, Interpreters and Tools 1Amr Rashed, 2Bedir Yousif, 3Ahmed Shaban Samra 1Higher studies Deanship, Taif university, Taif, Saudi Arabia 2Communication and Electronics Department, Faculty of engineering, Kafrelsheikh University, Egypt 3Communication and Electronics Department, Faculty of engineering, Mansoura University, Egypt Abstract: FPGAs have achieved quick acceptance, spread and growth over the past years because they can be applied to a variety of applications. Some of these applications includes: random logic, bioinformatics, video and image processing, device controllers, communication encoding, modulation, and filtering, limited size systems with RAM blocks, and many more. For example, for video and image processing application it is very difficult and time consuming to use traditional HDL languages, so it’s obligatory to search for other efficient, synthesis tools to implement your design. The question is what is the best comparable language or tool to implement desired application. Also this research is very helpful for language developers to know strength points, weakness points, ease of use and efficiency of each tool or language. This research faced many challenges one of them is that there is no complete reference of all FPGA languages and tools, also available references and guides are few and almost not good. Searching for a simple example to learn some of these tools or languages would be a time consuming. This paper represents a review study or guide of almost all PLD's languages, interpreters and tools that can be used for programming, simulating and synthesizing PLD's for analog, digital & mixed signals and systems supported with simple examples. -
AN5072: Introduction to Embedded Graphics – Application Note
Freescale Semiconductor Document Number: AN5072 Application Note Rev 0, 02/2015 Introduction to Embedded Graphics with Freescale Devices by: Luis Olea and Ioseph Martinez Contents 1 Introduction 1 Introduction................................................................1 The purpose of this application note is to explain the basic 1.1 Graphics basic concepts.............. ...................1 concepts and requirements of embedded graphics applications, 2 Freescale graphics devices.............. ..........................7 helping software and hardware engineers easily understand the fundamental concepts behind color display technology, which 2.1 MPC5606S.....................................................7 is being expected by consumers more and more in varied 2.2 MPC5645S.....................................................8 applications from automotive to industrial markets. 2.3 Vybrid.............................................................8 This section helps the reader to familiarize with some of the most used concepts when working with graphics. Knowing 2.4 MAC57Dxx....................... ............................ 8 these definitions is basic for any developer that wants to get 2.5 Kinetis K70......................... ...........................8 started with embedded graphics systems, and these concepts apply to any system that handles graphics irrespective of the 2.6 QorIQ LS1021A................... ......................... 9 hardware used. 2.7 i.MX family........................ ........................... 9 2.8 Quick -
3D Graphics Video
NVIDIA GEFORCE GTX 200 GPU DATASHEET 3D Graphics nd · 2 generation unified architecture 1 · Up to 240 processor cores · Next generation geometry shading and stream out performance · Next generation dual issue · Next generation HW scheduler · NVIDIA GigaThread™ technology with increased number of threads · 2x registers · Full support for Microsoft DirectX 10.0 Shader Model 4.0 and OpenGL 2.1 APIs · Full 128-bit floating point precision through the entire rendering pipeline · Lumenex™ Engine · 16× full screen antialiasing · Transparent multisampling and transparent supersampling · 16× angle independent anisotropic filtering · 128-bit floating point high dynamic-range (HDR) lighting with antialiasing · 32-bit per component floating point texture filtering and blending · Full speed frame buffer blending · Advanced lossless compression algorithms for color, texture, and z-data · Support for normal map compression · Z-cull · Early-Z Video 2 · PureVideo HD® Technology · Dedicated on-chip video processor · High-definition H.264, VC-1, MPEG2, and WMV9 decode acceleration · Blu-ray dual-stream hardware acceleration (supporting HD picture-in-picture playback) 3 · HDCP capable up to 2560×1600 resolution · Advanced spatial-temporal de-interlacing · Noise Reduction · Edge Enhancement · Bad Edit Correction · Inverse telecine (2:2 and 3:2 pull-down correction) · High-quality scaling · Video color correction · Microsoft Video Mixing Renderer (VMR) support · Dynamic Contrast and Tone Enhancements NVIDIA GEFORCE GTX 200 GPU DATASHEET NVIDIA Technology 4 -
Efpgas : Architectural Explorations, System Integration & a Visionary Industrial Survey of Programmable Technologies Syed Zahid Ahmed
eFPGAs : Architectural Explorations, System Integration & a Visionary Industrial Survey of Programmable Technologies Syed Zahid Ahmed To cite this version: Syed Zahid Ahmed. eFPGAs : Architectural Explorations, System Integration & a Visionary Indus- trial Survey of Programmable Technologies. Micro and nanotechnologies/Microelectronics. Université Montpellier II - Sciences et Techniques du Languedoc, 2011. English. tel-00624418 HAL Id: tel-00624418 https://tel.archives-ouvertes.fr/tel-00624418 Submitted on 16 Sep 2011 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. Université Montpellier 2 (UM2) École Doctorale I2S LIRMM (Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier) Domain: Microelectronics PhD thesis report for partial fulfillment of requirements of Doctorate degree of UM2 Thesis conducted in French Industrial PhD (CIFRE) framework between: Menta & LIRMM lab (Dec.2007 – Feb. 2011) in Montpellier, FRANCE “eFPGAs: Architectural Explorations, System Integration & a Visionary Industrial Survey of Programmable Technologies” eFPGAs: Explorations architecturales, integration système, et une enquête visionnaire industriel des technologies programmable by Syed Zahid AHMED Presented and defended publically on: 22 June 2011 Jury: Mr. Guy GOGNIAT Prof. at STICC/UBS (Lorient, FRANCE) President Mr. Habib MEHREZ Prof. at LIP6/UPMC (Paris, FRANCE) Reviewer Mr.