'Texture memory' presentation slideshows

Dave Shreiner Alan Commike Brad Grantham Bob Kuehne

1.88k views • 174 slides

GPU Programming

GPU Programming. Assignment 4. Consists of two programming assignments Concurrency GPU programming Requires a computer with a CUDA/ OpenCL / DirectCompute compatible GPU Due Jun 07 We have no final exams. GPU Resources. Download CUDA toolkit from the web Very good text book:

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Graphics Programming on the Web with WebCL

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Issues in Distributed Computing

546 views • 38 slides

OpenGL Performance Tuning

OpenGL Performance Tuning. John Spitzer NVIDIA Corporation. Overview. Understand the stages of the graphics pipeline Cherchez la bottleneck Once found, either eliminate or balance. Simplified Graphics Pipeline. CPU. Geometry Storage. Geometry Processor. Rasterizer. Fragment Processor.

501 views • 37 slides

Micro Benchmarking CUDA Final Project Presentation

Steven Sparks Kibeom Kim. Micro Benchmarking CUDA Final Project Presentation. Micro Benchmarking - Objectives. Measure the texture cache parameters Latency Capacity Associativity Measure the memory bandwidth Texture global and cache memory Normal global memory Shared memory.

483 views • 37 slides

Christmas Break

457 views • 33 slides

Graphics Hardware and Software using Linux

Graphics Hardware and Software using Linux. Ray Gasser, rayg@bu.edu Graphics Programmer/Analyst Scientific Computing and Visualization Group Boston University. Introduction. Agenda Why Linux/Intel? Hardware Video Cards Processors I/O and Memory Software System (OS, X, drivers)

503 views • 33 slides

Outline

Towards Acceleration of Fault Simulation Using Graphics Processing Units Kanupriya Gulati Sunil P. Khatri Department of ECE Texas A&M University, College Station. Outline. Introduction Technical Specifications of the GPU CUDA Programming Model Approach Experimental Setup and Results

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Intensity model with blur effect on GPUs applied to large-scale star simulators

Intensity model with blur effect on GPUs applied to large-scale star simulators. Chao Li Institute of Software, Chinese Academy of Sciences. Outline. Background and Motivation Model description Our simulators Evaluation Conclusion Future work. Background.

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Outline

Accelerating Statistical Static Timing Analysis Using Graphics Processing Units Kanupriya Gulati & Sunil P. Khatri Department of ECE Texas A&M University, College Station. Outline. Introduction Technical Specifications of the GPU CUDA Programming Model Approach

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MIDeA :A Multi-Parallel Instrusion Detection Architecture

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L5: Memory Hierarchy Optimization III, Data Placement, cont. and Memory Bandwidth Optimizations

L5: Memory Hierarchy Optimization III, Data Placement, cont. and Memory Bandwidth Optimizations. CS6235. Administrative. Next assignment available Next three slides Goals of assignment: simple memory hierarchy management block-thread decomposition tradeoff Due Tuesday, Feb. 7, 5PM

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CS179: GPU Programming

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ME964 High Performance Computing for Engineering Applications

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Accelerating Error Correction in High-Throughput Short-Read DNA Sequencing Data with CUDA

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Introduction to 3D computer graphics part 2

Introduction to 3D computer graphics part 2. Viewing pipeline Multi-processor implementation GPU architecture GPU algorithms. fragment/ pixel processing. geometry processing. CPU. 1 M polygons/s. 500 Mflops. 100 Mpix/s. 5000 Mips. Viewing pipeline. model from database.

228 views • 13 slides