AMD APP SDK V2.8.1 Developer Release Notes
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Small Form Factor 3D Graphics for Your Pc
VisionTek Part# 900701 PRODUCTIVITY SERIES: SMALL FORM FACTOR 3D GRAPHICS FOR YOUR PC The VisionTek Radeon R7 240SFF graphics card offers a perfect balance of performance, features, and affordability for the gamer seeking a complete solution. It offers support for the DIRECTX® 11.2 graphics standard and 4K Ultra HD for stunning 3D visual effects, realistic lighting, and lifelike imagery. Its Short Form Factor design enables it to fit into the latest Low Profile desktops and workstations, yet the R7 240SFF can be converted to a standard ATX design with the included tall bracket. With 2GB of DDR3 memory and award-winning Graphics Core Next (GCN) architecture, and DVI-D/HDMI outputs, the VisionTek Radeon R7 240SFF is big on features and light on your wallet. RADEON R7 240 SPECS • Graphics Engine: RADEON R7 240 • Video Memory: 2GB DDR3 • Memory Interface: 128bit • DirectX® Support: 11.2 • Bus Standard: PCI Express 3.0 • Core Speed: 780MHz • Memory Speed: 800MHz x2 • VGA Output: VGA* • DVI Output: SL DVI-D • HDMI Output: HDMI (Video/Audio) • UEFI Ready: Support SYSTEM REQUIREMENTS • PCI Express® based PC is required with one X16 lane graphics slot available on the motherboard. • 400W (or greater) power supply GCN Architecture: A new design for AMD’s unified graphics processing and compute cores that allows recommended. 500 Watt for AMD them to achieve higher utilization for improved performance and efficiency. CrossFire™ technology in dual mode. • Minimum 1GB of system memory. 4K Ultra HD Support: Experience what you’ve been missing even at 1080P! With support for 3840 x • Installation software requires CD-ROM 2160 output via the HDMI port, textures and other detail normally compressed for lower resolutions drive. -
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 -
Monte Carlo Evaluation of Financial Options Using a GPU a Thesis
Monte Carlo Evaluation of Financial Options using a GPU Claus Jespersen 20093084 A thesis presented for the degree of Master of Science Computer Science Department Aarhus University Denmark 02-02-2015 Supervisor: Gerth Brodal Abstract The financial sector has in the last decades introduced several new fi- nancial instruments. Among these instruments, are the financial options, which for some cases can be difficult if not impossible to evaluate analyti- cally. In those cases the Monte Carlo method can be used for pricing these instruments. The Monte Carlo method is a computationally expensive al- gorithm for pricing options, but is at the same time an embarrassingly parallel algorithm. Modern Graphical Processing Units (GPU) can be used for general purpose parallel-computing, and the Monte Carlo method is an ideal candidate for GPU acceleration. In this thesis, we will evaluate the classical vanilla European option, an arithmetic Asian option, and an Up-and-out barrier option using the Monte Carlo method accelerated on a GPU. We consider two scenarios; a single option evaluation, and a se- quence of a varying amount of option evaluations. We report performance speedups of up to 290x versus a single threaded CPU implementation and up to 53x versus a multi threaded CPU implementation. 1 Contents I Theoretical aspects of Computational Finance 5 1 Computational Finance 5 1.1 Options . .7 1.1.1 Types of options . .7 1.1.2 Exotic options . .9 1.2 Pricing of options . 11 1.2.1 The Black-Scholes Partial Differential Equation . 11 1.2.2 Solving the PDE and pricing vanilla European options . -
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. -
Deep Dive: Asynchronous Compute
Deep Dive: Asynchronous Compute Stephan Hodes Developer Technology Engineer, AMD Alex Dunn Developer Technology Engineer, NVIDIA Joint Session AMD NVIDIA ● Graphics Core Next (GCN) ● Maxwell, Pascal ● Compute Unit (CU) ● Streaming Multiprocessor (SM) ● Wavefronts ● Warps 2 Terminology Asynchronous: Not independent, async work shares HW Work Pairing: Items of GPU work that execute simultaneously Async. Tax: Overhead cost associated with asynchronous compute 3 Async Compute More Performance 4 Queue Fundamentals 3 Queue Types: 3D ● Copy/DMA Queue ● Compute Queue COMPUTE ● Graphics Queue COPY All run asynchronously! 5 General Advice ● Always profile! 3D ● Can make or break perf ● Maintain non-async paths COMPUTE ● Profile async on/off ● Some HW won’t support async ● ‘Member hyper-threading? COPY ● Similar rules apply ● Avoid throttling shared HW resources 6 Regime Pairing Good Pairing Poor Pairing Graphics Compute Graphics Compute Shadow Render Light culling G-Buffer SSAO (Geometry (ALU heavy) (Bandwidth (Bandwidth limited) limited) limited) (Technique pairing doesn’t have to be 1-to-1) 7 - Red Flags Problem/Solution Format Topics: ● Resource Contention - ● Descriptor heaps - ● Synchronization models ● Avoiding “async-compute tax” 8 Hardware Details - ● 4 SIMD per CU ● Up to 10 Wavefronts scheduled per SIMD ● Accomplish latency hiding ● Graphics and Compute can execute simultanesouly on same CU ● Graphics workloads usually have priority over Compute 9 Resource Contention – Problem: Per SIMD resources are shared between Wavefronts SIMD executes -
Contributions of Hybrid Architectures to Depth Imaging: a CPU, APU and GPU Comparative Study
Contributions of hybrid architectures to depth imaging : a CPU, APU and GPU comparative study Issam Said To cite this version: Issam Said. Contributions of hybrid architectures to depth imaging : a CPU, APU and GPU com- parative study. Hardware Architecture [cs.AR]. Université Pierre et Marie Curie - Paris VI, 2015. English. NNT : 2015PA066531. tel-01248522v2 HAL Id: tel-01248522 https://tel.archives-ouvertes.fr/tel-01248522v2 Submitted on 20 May 2016 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. THESE` DE DOCTORAT DE l’UNIVERSITE´ PIERRE ET MARIE CURIE sp´ecialit´e Informatique Ecole´ doctorale Informatique, T´el´ecommunications et Electronique´ (Paris) pr´esent´eeet soutenue publiquement par Issam SAID pour obtenir le grade de DOCTEUR en SCIENCES de l’UNIVERSITE´ PIERRE ET MARIE CURIE Apports des architectures hybrides `a l’imagerie profondeur : ´etude comparative entre CPU, APU et GPU Th`esedirig´eepar Jean-Luc Lamotte et Pierre Fortin soutenue le Lundi 21 D´ecembre 2015 apr`es avis des rapporteurs M. Fran¸cois Bodin Professeur, Universit´ede Rennes 1 M. Christophe Calvin Chef de projet, CEA devant le jury compos´ede M. Fran¸cois Bodin Professeur, Universit´ede Rennes 1 M.