Computer Architecture ELEC3441 Lecture 11 – Advanced Pipeline Dr. Hayden Kwok-Hay So Department of Electrical and Electronic Engineering Simple pipeline so far… n CPI of simple pipelined processor is always >= 1 • Commitsatmost1instructionpercycle n Stalling and wasted cycles increase CPI • Cachemiss • TLBmiss • pagefault • Branchmisprediction HKUEEE ENGG3441 – HS 2 Challenges […]
b’cuda_demo.tar.gz’ nvcc cuda_tutorial11.cu -o cuda_tutorial11.out #include #include /* This file can be downloaded from supercomputingblog.com. This is part of a series of tutorials that demonstrate how to use CUDA The tutorials will also demonstrate the speed of using CUDA */ // IMPORTANT NOTE: for this data size, your graphics card should have at least 512
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Parallel Memory Models CMPSC 450 Taxonomy of Parallel Computing Paradigms • SIMD – Single Instruction Multiple Data – A single instruction pipeline applied to multiple compute elements. Ex: Vector Processors, GPU Processing, MMX, SSE, AVX instruction sets. • MIMD – Multiple Instruction Multiple Data – Multiple instruction pipelines are working on multiple data streams concurrently.
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CUDA CMPSC 450 What is CUDA • Compute Unified Device Architecture • An extension of the C programming language created by nVidia. • Enables GPUs to execute programs written in C in an integrated host (CPU) + device (GPU) app C program • Execute “kernels” as a SIMT program • A dedicated hardware solution CMPSC
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b’cudaTut3PBSDemo.tar.gz’ #include #include #include /* This file can be downloaded from supercomputingblog.com. This is part of a series of tutorials that demonstrate how to use CUDA The tutorials will also demonstrate the speed of using CUDA */ // IMPORTANT NOTE: for this data size, your graphics card should have at least 256 megabytes of memory.
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Prefix Sums CMPSC 450 Definition: The all-prefix-sums operation takes a binary associative operator , and an ordered set of n elements and returns the ordered set [a0, a1, …, an−1], [a0,(a0 a1), …,(a0 a1 … an−1)]. CMPSC 450 Serial example • Make binary-associative operator ‘+’ b[0] = a[0]; for (i = 1; i < n;
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Hardware Platforms for IoT Syllabus This module will cover the following • What is a hardware platform • Types of memory • Power saving techniques • Types of sensors • Analog-to-digital conversion 2 © 2020 Arm Limited What is a hardware platform? A set of compatible physical components that determine the functionality of a device
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3/2/2021 CSE 473/573 ‘- Introduction to Computer Vision and Image Processing 1 FEATURE DESCRIPTORS Questions from Last Lecture? Homework 2 Due Thursday (3/4) Quiz Next Tuesday (3/9) Updated Schedule – P2 Assigned Next Tuesday 2/4)2 ‘- 1 3/2/2021 REVIEW: Feature descriptors • Disadvantage of patches as descriptors: • Small shifts can affect matching score a
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Expanded Perception and Interaction Centre Applied Hybrid Analytics and Computer Vision Application for Research and Industry Tomasz Bednarz Director @ EPICentre, UNSW | Simulation & Modelling CCC Lead, CSIRO + collaborators from CSIRO, UNSW, QUT, Kyushu University, JCU, ACEMS About Power of Simulation Source: https://twitter.com/northmantrader/status/905143410927034369 Role of visualisation • Visual Analytics and Automated/Statistical Methods are
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COMP5822M – Exercise 1.4 Resources 1 Project Updates 1 2 Vertex Buffers 2 3 Uniform Buffer & Descriptors 10 Copyright By PowCoder代写 加微信 powcoder 4 Textures 20 5 Second object 32 6 Depth buffer & testing 35 7 2nd pipeline & Blending 38 Exercise 4 introduces Vulkan resources, specifically buffers and textures. While textures are
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