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CUDA: Introduction

CUDA: Introduction

Christian Trefftz / Greg Wolffe Grand Valley State University Supercomputing 2008 Education Program. CUDA: Introduction. Terms. What is GPGPU? General-Purpose computing on a Graphics Processing Unit Using graphic hardware for non-graphic computations What is CUDA?

By JasminFlorian
(323 views)

I/O Management and Disk Scheduling (Chapter 11)

I/O Management and Disk Scheduling (Chapter 11)

I/O Management and Disk Scheduling (Chapter 11). Perhaps the messiest aspect of operating system design is input/output A wide variety of devices and many different applications of those devices. It is difficult to develop a general, consistent solution. Chapter Summary I/O devices

By mahina
(186 views)

Graphics Programming on the Web with WebCL

Graphics Programming on the Web with WebCL

Graphics Programming on the Web with WebCL. Mikaël Bourges-Sévenier , Motorola Mobility August 9, 2012. Over 32000 planks ;-) Blender/Bullet/ SmallLuxGPU OpenCL By Alain Ducharme “ Phymec ” http ://www.youtube.com/watch?v= 143k1fqPukk. Motivation. For compute intensive web applications

By dougal
(132 views)

Microprocessors

Microprocessors

Microprocessors. General Features To be Examined For Each Chip Jan 24 th , 2002. Memory Structure. Addressable units For example byte vs word addressable Most machines are 8-bit byte addressable Memory size Form of Addresses Usually a simple linear address 0 .. 2**N-1 But not always.

By zinnia
(96 views)

DuQu

DuQu

DuQu. Presented by Ravil Nazipov. In which countries DuQu was detected?. How it works?. Payload types. Info-stealer. List of running processes, information about the current user and the domain List of logical drives, including network drives Screenshots

By chynna
(146 views)

Using CUDA for High Performance Scientific Computing

Using CUDA for High Performance Scientific Computing

Using CUDA for High Performance Scientific Computing. Dana Schaa NUCAR Research Group Northeastern University. Outline. What is CUDA? Concepts and Terminology Program Design with CUDA Example Programs Ideal Characteristics for Graphics Processing. CUDA and nVidia.

By yovela
(154 views)

Memory System Performance in a NUMA Multicore Multiprocessor

Memory System Performance in a NUMA Multicore Multiprocessor

Memory System Performance in a NUMA Multicore Multiprocessor. Zoltan Majo and Thomas R. Gross Department of Computer Science ETH Zurich. Summary. NUMA multicore systems are unfair to local memory accesses Local execution sometimes suboptimal. Outline.

By gavivi
(147 views)

Scaled Weights in Plingeling

Scaled Weights in Plingeling

Scaled Weights in Plingeling. Daphne Gorman CMPS217. Introduction: Plingeling. Creates a single thread with the entire problem and then clones that thread Based off of Lingeling Memory efficiency “Portfolio solver” Formula and shared clauses all have their own local memory

By romney
(125 views)

ABAP Chapter 2

ABAP Chapter 2

ABAP Chapter 2. Report Statement Write & Format Statement Flow Control in ABAP Manipulating Character Data Report Driven : Page Report (List Header). List Processing. Report Header Report Listing (Body). Report Statement. * Syntax REPORT < report name >

By jin
(188 views)

Mutual exclusion

Mutual exclusion

Mutual exclusion. read/write variables. The Bakery Algorithm. The algorithm is similar with the read-modify-write algorithm. There is a queue: The process in the head is in critical section A new process is inserted in the tail. Algorithm outline.

By carlow
(129 views)

CUDA: Introduction

CUDA: Introduction

Christian Trefftz / Greg Wolffe Grand Valley State University Supercomputing 2008 Education Program. CUDA: Introduction. Terms. What is GPGPU? General-Purpose computing on a Graphics Processing Unit Using graphic hardware for non-graphic computations What is CUDA?

By falala
(139 views)

Performance

Performance

Performance. What hardware accelerators are you using/evaluating ? Cells in a Roadrunner configuration 8-way SPE threads w/ local memory, DMA & vector unit programming issues but tremendous flexibility Fast (25.6 GB/s) & large memory (4GB or larger)

By duman
(53 views)

Parallel and Multiprocessor Architectures

Parallel and Multiprocessor Architectures

Parallel and Multiprocessor Architectures. Chapter 9.4. By Eric Neto. Parallel & Multiprocessor Architecture. In making processors faster, we run into certain limitations. Physical Economic Solution: When necessary, use more processors, working in sync.

By neron
(119 views)

Block Design Review: Queue Manager and Scheduler

Block Design Review: Queue Manager and Scheduler

Block Design Review: Queue Manager and Scheduler. Amy M. Freestone Sailesh Kumar. V 1. Rsv (3b). Port (4b). Buffer Handle(24b). QM/Schd. Overview. Lookup. Hdr Format. Switch Tx. S W I T C H. Phy Int Rx. Key Extract. QM/Scheduler Function:

By barny
(72 views)

Accelerator-based Implementation of the Harris Algorithm

Accelerator-based Implementation of the Harris Algorithm

Accelerator-based Implementation of the Harris Algorithm. Claude TADONKI Mines ParisTech – CRI (Centre de Recherche en Informatique) Fontainebleau (France) claude.tadonki@mines-paristech.fr Joint work with Lionel Lacassagne, Elwardani Dadi, Mostafa El Daoudi.

By daria
(177 views)

COMPUTING HW REQUIREMENT

COMPUTING HW REQUIREMENT

COMPUTING HW REQUIREMENT. Enzo Papandrea. GEOFIT - MTR. With Geofit measurements from a full orbit are simultaneously processed A Geofit where P, T and VMR of H 2 O and O 3 are simultaneously retrieved increase the computing time. TIME OF SIMULATIONS.

By nash
(59 views)

AndeScore N1213-S

AndeScore N1213-S

AndeScore N1213-S. AndeScore™ N1213-S. CPU Core 32bit CPU Single issue with 8-stage pipeline AndeStar™ ISA with 16-/32-bit intermixable instructions to reduce code size Dynamic branch prediction to reduce branch penalties 32/64/128/256 BTB Configurability for customers

By alia
(132 views)

Workshop on Reduction

Workshop on Reduction

Optimizing Simple CUDA and OpenCL Kernels Chris Szalwinski December 5 2013. Workshop on Reduction. Overview. Reduction Algorithm Terminology – CUDA and OpenCL Test Problem – Dot Product Test Parameters Execution Configuration Divergence Register Storage. Reduction Algorithm.

By teneil
(92 views)

Architectures of Digital Information Systems Part 2: Programmable I/O and Multiprocessors

Architectures of Digital Information Systems Part 2: Programmable I/O and Multiprocessors

Architectures of Digital Information Systems Part 2: Programmable I/O and Multiprocessors. dr.ir. A.C. Verschueren Eindhoven University of Technology Section of Digital Information Systems. Programmable input/output controllers.

By zoie
(127 views)

System Architecture: Big Iron (NUMA)

System Architecture: Big Iron (NUMA)

System Architecture: Big Iron (NUMA). Joe Chang jchang6@yahoo.com www.qdpma.com. About Joe Chang. SQL Server Execution Plan Cost Model True cost structure by system architecture Decoding statblob (distribution statistics) SQL Clone – statistics-only database Tools

By beyla
(140 views)

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