Quickspecs AMD Firestream Compute Module Overview
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AMD Firestream™ 9350 GPU Compute Accelerator
AMD FireStream™ 9350 GPU Compute Accelerator High Density Server GPU Acceleration The AMD FireStream™ 9350 GPU compute accelerator card offers industry- leading performance-per-watt in a highly dense, single-slot form factor. This AMD FireStream 9350 low-profile GPU card is designed for scalable high performance computing > Heterogeneous computing that (HPC) systems that require density and power efficiency. The AMD FireStream leverages AMD GPUs and x86 CPUs 9350 is ideal for a wide range of HPC applications across several industries > High performance per watt at 2.9 including Finance, Energy (Oil and Gas), Geosciences, Life Sciences, GFLOPS / Watt Manufacturing (CAE, CFD, etc.), Defense, and more. > Industry’s most dense server GPU card 1 Utilizing the multi-billion-transistor ASICs developed for AMD Radeon™ graphics > Low profile and passively cooled cards, AMD’s FireStream 9350 cards provide maximum performance-per-slot > Massively parallel, programmable GPU and are designed to meet demanding performance and reliability requirements architecture of HPC systems that can scale to thousands of nodes. AMD FireStream 9350 > Open standard OpenCL™ and cards include a single DisplayPort output. DirectCompute2 AMD FireStream 9350 cards can be used in scalable servers, blades, PCIe® > 2.0 TFLOPS, Single-Precision Peak chassis, and are available from many leading server OEMs and HPC solution > 400 GFLOPS, Double-Precision Peak providers. > 2GB GDDR5 memory Priced competitively, AMD FireStream GPUs offer unparalleled performance > Industry’s only Single-Slot PCIe® Accelerator and value for high performance computing. > PCI Express® 2.1 Compliant Note: For workstation and server > AMD Accelerated Parallel Processing installations that require active (APP) Technology SDK with OpenCL3 cooling, AMD FirePro™ Professional > 3-year planned availability; 3-year Graphics boards are software- limited warranty compatible and offer comparable features. -
ATI Radeon™ HD 4870 Computation Highlights
AMD Entering the Golden Age of Heterogeneous Computing Michael Mantor Senior GPU Compute Architect / Fellow AMD Graphics Product Group [email protected] 1 The 4 Pillars of massively parallel compute offload •Performance M’Moore’s Law Î 2x < 18 Month s Frequency\Power\Complexity Wall •Power Parallel Î Opportunity for growth •Price • Programming Models GPU is the first successful massively parallel COMMODITY architecture with a programming model that managgped to tame 1000’s of parallel threads in hardware to perform useful work efficiently 2 Quick recap of where we are – Perf, Power, Price ATI Radeon™ HD 4850 4x Performance/w and Performance/mm² in a year ATI Radeon™ X1800 XT ATI Radeon™ HD 3850 ATI Radeon™ HD 2900 XT ATI Radeon™ X1900 XTX ATI Radeon™ X1950 PRO 3 Source of GigaFLOPS per watt: maximum theoretical performance divided by maximum board power. Source of GigaFLOPS per $: maximum theoretical performance divided by price as reported on www.buy.com as of 9/24/08 ATI Radeon™HD 4850 Designed to Perform in Single Slot SP Compute Power 1.0 T-FLOPS DP Compute Power 200 G-FLOPS Core Clock Speed 625 Mhz Stream Processors 800 Memory Type GDDR3 Memory Capacity 512 MB Max Board Power 110W Memory Bandwidth 64 GB/Sec 4 ATI Radeon™HD 4870 First Graphics with GDDR5 SP Compute Power 1.2 T-FLOPS DP Compute Power 240 G-FLOPS Core Clock Speed 750 Mhz Stream Processors 800 Memory Type GDDR5 3.6Gbps Memory Capacity 512 MB Max Board Power 160 W Memory Bandwidth 115.2 GB/Sec 5 ATI Radeon™HD 4870 X2 Incredible Balance of Performance,,, Power, Price -
Download Radeon Grpadhics Catalylist and Driver AMD Catalyst Graphics Driver 13.4 X64
download radeon grpadhics catalylist and driver AMD Catalyst Graphics Driver 13.4 x64. Fixes : - With the Radeon HD7790 graphics card, corruption may be seen in the game Tomb Raider with TressFX enabled - Texture flickering may be observed in DirectX 9.0c enabled applications - Corruption observed in Tomb Raider with TressFX enabled for AMD Crossfire and single GPU system configurations - Corruption observed on objects and textures in the game, Call of Duty – Black Ops 2 - Corruption observed in the game, Alan Wake (DirectX 9 Mode) when attempting to change in-game settings with Stereoscopic 3D using Tridef - Corruption observed on textures in the game, Battle Field: Bad Company 2 with forced anti-aliasing enabled - Adobe Photoshop CS6 experiences screen flicker under Windows 8 based system - Horizontal line corruption may be observed with forced anti-aliasing enabled in the game, Dishonored - System hang may occur when scrolling through the game selection menu in the game, DiRT 3 - F1 2012 may crash to desktop on systems supporting AMD PowerXpress (Enduro) Technology - Support added for AMD Radeon HD7790 and AMD Radeon HD 7990 - Catalyst Driver optimizations to improve performance in Far Cry 3, Crysis 3, and 3DMark - Significantly improves latency performance in Skyrim, Boderlands 2, Guild Wars 2, Tomb Raider and Hitman Absolution. Performance gains seen with the entire AMD Radeon HD 7000 Series for the following: - Batman Arkham City (1920x1200): Performance improvements up to 5% - Borderlands 2 (2560x1600): Performance improvements -
AMD APP SDK Developer Release Notes
AMD APP SDK v3.0 Beta Developer Release Notes 1 What’s New in AMD APP SDK v3.0 Beta 1.1 New features in AMD APP SDK v3.0 Beta AMD APP SDK v3.0 Beta includes the following new features: OpenCL 2.0: There are 20 samples that demonstrate various features of OpenCL 2.0 such as Shared Virtual Memory, Platform Atomics, Device-side Enqueue, Pipes, New workgroup built-in functions, Program Scope Variables, Generic Address Space, and OpenCL 2.0 image features. For the complete list of the samples, see the AMD APP SDK Samples Release Notes (AMD_APP_SDK_Release_Notes_Samples.pdf) document. Support for Bolt 1.3 library. 6 additional samples that demonstrate various APIs in the Bolt C++ AMP library. One new sample that demonstrates the consumption of SPIR 1.2 binary. Enhancements and bug fixes in several samples. A lightweight installer that supports the following features: Customized online installation Ability to download the full installer for install and distribution 1.2 New features for AMD CodeXL version 1.6 The following new features in AMD CodeXL version 1.6 provide the following improvements to the developer experience: GPU Profiler support for OpenCL 2.0 API-level debugging for OpenCL 2.0 Power Profiling For information about CodeXL and about how to use CodeXL to gather performance data about your OpenCL application, such as application traces and timeline views, see the CodeXL home page. Developer Release Notes 1 of 4 2 Important Notes OpenCL 2.0 runtime support is limited to 64-bit applications running on 64-bit Windows and Linux operating systems only. -
The Compute Shader
AMD Entering the Golden Age of Heterogeneous Computing Michael Mantor Senior GPU Compute Architect / Fellow AMD Graphics Product Group [email protected] 1 The 4 Pillars of massively parallel compute offload •Performance M’Moore’s Law Î 2x < 18 Month s Frequency\Power\Complexity Wall •Power Parallel Î Opportunity for growth •Price • Programming Models GPU is the first successful massively parallel COMMODITY architecture with a programming model that managgped to tame 1000’s of parallel threads in hardware to perform useful work efficiently 2 Quick recap of where we are – Perf, Power, Price ATI Radeon™ HD 4850 4x Performance/w and Performance/mm² in a year ATI Radeon™ X1800 XT ATI Radeon™ HD 3850 ATI Radeon™ HD 2900 XT ATI Radeon™ X1900 XTX ATI Radeon™ X1950 PRO 3 Source of GigaFLOPS per watt: maximum theoretical performance divided by maximum board power. Source of GigaFLOPS per $: maximum theoretical performance divided by price as reported on www.buy.com as of 9/24/08 ATI Radeon™HD 4850 Designed to Perform in Single Slot SP Compute Power 1.0 T-FLOPS DP Compute Power 200 G-FLOPS Core Clock Speed 625 Mhz Stream Processors 800 Memory Type GDDR3 Memory Capacity 512 MB Max Board Power 110W Memory Bandwidth 64 GB/Sec 4 ATI Radeon™HD 4870 First Graphics with GDDR5 SP Compute Power 1.2 T-FLOPS DP Compute Power 240 G-FLOPS Core Clock Speed 750 Mhz Stream Processors 800 Memory Type GDDR5 3.6Gbps Memory Capacity 512 MB Max Board Power 160 W Memory Bandwidth 115.2 GB/Sec 5 ATI Radeon™HD 4870 X2 Incredible Balance of Performance,,, Power, Price -
Catalyst™ Software Suite Version 9.5 Release Notes
Catalyst™ Software Suite Version 9.5 Release Notes This release note provides information on the latest posting of AMD’s industry leading software suite, Catalyst™. This particular software suite updates both the AMD Display Driver, and the Catalyst™ Control Center. This unified driver has been further enhanced to provide the highest level of power, performance, and reliability. The AMD Catalyst™ software suite is the ultimate in performance and stability. For exclusive Catalyst™ updates follow Catalyst Maker on Twitter. This release note provides information on the following: z Web Content z AMD Product Support z Operating Systems Supported z New Features z Performance Improvements z Resolved Issues for the Windows Vista Operating System z Resolved Issues for the Windows XP Operating System z Resolved Issues for the Windows 7 Operating System z Known Issues Under the Windows Vista Operating System z Known Issues Under the Windows XP Operating System z Known Issues Under the Windows 7 Operating System z Installing the Catalyst™ Vista Software Driver z Catalyst™ Crew Driver Feedback ATI Catalyst™ Release Note Version 9.5 1 Web Content The Catalyst™ Software Suite 9.5 contains the following: z Radeon™ display driver 8.612 z HydraVision™ for both Windows XP and Vista z HydraVision™ Basic Edition (Windows XP only) z WDM Driver Install Bundle z Southbridge/IXP Driver z Catalyst™ Control Center Version 8.612 Caution: The Catalyst™ software driver and the Catalyst™ Control Center can be downloaded independently of each other. However, for maximum stability and performance AMD recommends that both components be updated from the same Catalyst™ release. -
AMD APP SDK V2.9.1 Developer Release Notes
AMD APP SDK v2.9.1 Developer Release Notes 1 What’s New in AMD APP SDK v2.9.1 1.1 New features in AMD APP SDK v2.9.1 AMD APP SDK v2.9.1 includes the following new features: The AMD APP SDK can now be installed on Linux with root as well as non-root permissions. The installation logs display additional details about the status of the installation. Several samples have been enhanced. All the samples are now compatible with the gcc version, 4.8.1. The APARAPI samples have been updated to work with the latest APARAPI (OpenCL trunk) library. The OpenCV-CL samples now work with the OpenCV 2.4.9 library. The AMD APP SDK Bolt samples have been updated to work with the Bolt 1.2 library. For information about the features released in AMD APP SDK v2.9, see the AMD APP SDK v2.9 Developer Release Notes document. 1.2 Key features supported in the AMD Catalyst 14.4 driver Support for Kaveri graphics AMD Radeon R5/R6/R7 Support for AMD Radeon R9 295X Full support for OpenGL 4.4 Support for the following operating systems: Windows 8.1 (32- and 64-bit versions) Windows 7 (32- and 64-bit versions with SP1 or higher) 1.3 New features for AMD CodeXL version 1.4 The following new features for AMD CodeXL version 1.4 provide the following improvements to the developer experience: Microsoft Visual Studio 2013 CodeXL Extension New Shader Analyzer Support for Volcanic Islands family GPUs: debugging, profiling and analyzing. -
Lewis University Dr. James Girard Summer Undergraduate Research Program 2021 Faculty Mentor - Project Application
Lewis University Dr. James Girard Summer Undergraduate Research Program 2021 Faculty Mentor - Project Application Exploring the Use of High-level Parallel Abstractions and Parallel Computing for Functional and Gate-Level Simulation Acceleration Dr. Lucien Ngalamou Department of Engineering, Computing and Mathematical Sciences Abstract System-on-Chip (SoC) complexity growth has multiplied non-stop, and time-to- market pressure has driven demand for innovation in simulation performance. Logic simulation is the primary method to verify the correctness of such systems. Logic simulation is used heavily to verify the functional correctness of a design for a broad range of abstraction levels. In mainstream industry verification methodologies, typical setups coordinate the validation e↵ort of a complex digital system by distributing logic simulation tasks among vast server farms for months at a time. Yet, the performance of logic simulation is not sufficient to satisfy the demand, leading to incomplete validation processes, escaped functional bugs, and continuous pressure on the EDA1 industry to develop faster simulation solutions. In this research, we will explore a solution that uses high-level parallel abstractions and parallel computing to boost the performance of logic simulation. 1Electronic Design Automation 1 1 Project Description 1.1 Introduction and Background SoC complexity is increasing rapidly, driven by demands in the mobile market, and in- creasingly by the fast-growth of assisted- and autonomous-driving applications. SoC teams utilize many verification technologies to address their complexity and time-to-market chal- lenges; however, logic simulation continues to be the foundation for all verification flows, and continues to account for more than 90% [10] of all verification workloads. -
Before the Web There Was Gopher
Before the Web There Was Gopher Philip L. Frana Charles Babbage Institute The World Wide Web, universally well known today, was preceded by an efficient software tool that was fondly named Gopher. The Internet Gopher, much like the Web, enabled users to obtain information quickly and easily. Why, then, did it disappear but the Web did not? Gopher faded into obscurity for two main reasons: hypertext and commerce. Before the Web there was Gopher, a nearly anymore, despite the efforts of a handful of defunct Internet application protocol and asso- individuals to revitalize the protocol. Why did ciated client and server software.1 In the early Gopher fail? Many Gopher aficionados have a 1990s, Gopher burrowed a crucial path ready answer: pretty pictures. For them, the through a perceived bottleneck on the Web won and Gopher lost because the Web Information Superhighway. Internet Gopher could display vibrant images of, for example, passed away as a technological and social phe- hand-woven Turkish rugs, animated glyphs of nomenon quickly: Its inventors released mice stuffing email into virtual mailboxes, and Gopher in 1991. Within three years, the World blinking advertising banners. Clearly, the Wide Web had bypassed it. Most people who “Gopher faithful”—as they are often called— surf the Web today have no idea what Gopher are right about the importance of pictures. is, but in the 1990s it helped usher in a new age People get serious when money is at stake, and of user-friendly access to a rapidly growing uni- in the early 1990s lots of people came to accept verse of online information. -
Here Comes Everybody by Clay Shirky
HERE COMES EVERYBODY THE POWER OF ORGANIZING WITHOUT ORGANIZATIONS CLAY SHIRKY ALLEN LANE an imprint of PENGUIN BOOKS ALLEN LANE Published by the Penguin Group Penguin Books Ltd, 80 Strand, London we2R ORL, England Penguin Group IUSA) Inc., 375 Hudson Street, New York, New York 10014, USA Penguin Group ICanada), 90 Eglinton Avenue East, Suite 700, Toronto, Ontario, Canada M4P 2Y3 la division of Pearson Penguin Canada Inc.) Penguin Ireland, 25 St Stephen's Green, Dublin 2, Ireland la division of Penguin Books Ltd) Penguin Group IAustralia), 250 Camberwell Road, Camberwell. Victoria 3124. Austra1ia (a division of Pearson Australia Group Pty Ltd) Penguin Books India Pvt Ltd, II Community Centre, Panchsheel Park. New Delhi - 110 017, India Penguin Group INZ), 67 Apollo Drive, Rosedale, North Shore 0632, New Zealand la division of Pearson New Zealand Ltd) Penguin Books ISouth Africa) IPty) Ltd, 24 Sturdee Avenue, Rosebank, Johannesburg 2196, South Africa Penguin Books Ltd, Registered Offices: 80 Strand, London we2R ORL, England www.penguin.com First published in the United States of America by The Penguin Press, a member of Penguin Group (USA) Inc. 2008 First published in Great Britain by Allen Lane 2008 Copyright © Clay Shirky, 2008 The moral right of the author has been asserted AU rights reserved Without limiting the rights under copyright reserved above, no part of this publication may be reproduced, stored in or introduced into a retrieval system, or transmitted, in any form or by any means (electronic, mechanical, photocopying, recording or otherwise). without the prior written permission of both the copyright owner and the above publisher of this book Printed in Great Britain by Clays Ltd, St Ives pic A CI P catalogue record for this book is available from the British Library www.greenpenguin.co.uk Penguin Books is committed (0 a sustainable future D MIXed Sources for our business, our readers and our planer. -
ATI Stream Computing Update
Stream Computing on ATI Radeon™ Embedded Graphics Processors Peter Mandl Sr. Product Mgr, Embedded Graphics January 2010 1 Stream Computing Harnessing the Computational Power of GPUs • Hundreds of processing elements in a Graphics Processor Unit (GPU) • Enormous computational capability for data parallel workloads • Enables significant performance/watt and performance/$ improvements • Works together with the CPU Software Applications Graphics Workloads Serial and Task Parallel Data Parallel Workloads Workloads 2 ATI Stream Technology is… Heterogeneous: Developers leverage AMD GPUs and CPUs for optimal application performance and user experience High performance: Massively parallel, programmable GPU architecture enables superior performance and power efficiency Industry Standards: OpenCL™ and DirectCompute 11 enable cross- platform development Gaming Digital Content Productivity Creation Sciences Government Engineering 3 The World’s Most Efficient GPU* 16 14 14.47 GFLOPS/W 12 GFLOPS/W GFLOPS/mm2 10 7.50 8 4.50 7.90 6 GFLOPS/mm2 2.01 2.21 4 4.56 1.07 2.24 2 0.42 1.06 0.92 0 Nov-05 Jan-06 Sep-07 Nov-07 Jun-08 Oct-09 ATI Radeon™ ATI Radeon™ ATI Radeon™ HD ATI Radeon™ HD ATI Radeon™ HD ATI Radeon™ HD X1800 XT X1900 XTX 2900 PRO 3870 4870 5870 *Based on comparison of consumer client single-GPU configurations as of 12/08/09. ATI Radeon™ HD 5870 provides 4 14.47 GFLOPS/W and 7.90 GFLOPS/mm2 vs. NVIDIA GTX 285 at 5.21 GFLOPS/W and 2.26 GFLOPS/mm2. Enhancing GPUs for Computation RV770 Architecture • 800 stream processing units • Fast double-precision -
AMD APP SDK V2.8.1 Developer Release Notes
AMD APP SDK v2.8.1 Developer Release Notes 1 What’s New in AMD APP SDK v2.8.1 1.1 New features in AMD APP SDK v2.8.1 AMD APP SDK v2.8.1 includes the following new features: Bolt: With the launch of Bolt 1.0, several new samples have been added to demonstrate the use of the features of Bolt 1.0. These features showcase the use of valuable Bolt APIs such as scan, sort, reduce and transform. Other new samples highlight the ease of porting from STL and the performance benefits achieved over equivalent STL implementations. Other samples demonstrate the different fallback options in Bolt 1.0 when no GPU is available. These options include a fallback to multicore-CPU if TBB libraries are installed, or falling all the way back to serial-CPU if needed to ensure your code runs correctly on any platform. OpenCV: AMD has been working closely with the OpenCV open source community to add heterogeneous acceleration capability to the world’s most popular computer vision library. These changes are already integrated into OpenCV and are readily available for developers who want to improve the performance and efficiency of their computer vision applications. The new samples illustrate these improvements and highlight how simple it is to include them in your application. For information on the latest OpenCV enhancements, see Harris’ blog. GCN: AMD recently launched a new Graphics Core Next (GCN) Architecture on several AMD products. GCN is based on a scalar architecture versus the VLIW vector architecture of prior generations, so carefully hand-tuned vectorization to optimize hardware utilization is no longer needed.