CMPSC 450 Concurrent Scientific Programming Introduction CMPSC 450 Welcome to the class! • Class meets MWF 8-8:50AM on Zoom • Office hours • Tuesdays and Thursdays 8PM – 9PM. On Zoom. • By appointment • Email: use Canvas • About me: • Master of Engineering, CSE, Penn State 2001 • 20 years industry experience • […]
GPU Programming – Exercise 2: Reductions 1 Introduction This exercise is about how to perform reductions, in particular to perform dot products of really large vectors. Operations such as these are very common, but represent a challenge for many-core systems, such as GPUs. As long as sub-tasks can be performed in isolation, it is usually
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#include #include #include #include Copyright By PowCoder代写 加微信 powcoder #include // kernel routine __global__ void my_first_kernel(float *x) int tid = threadIdx.x + blockDim.x*blockIdx.x; x[tid] = (float)threadIdx.x; // main code int main(int argc, const char **argv) // set number of blocks, and threads per block int nblocks = 2; int nthreads = 8; int nsize =
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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CMPSC 450 definitions CMPSC 450 What is a ‘parallel computer’? • A parallel computer consists of a number of tightly-coupled compute elements that cooperatively solve a problem. • Example of `tight coupling’: shared caches, shared main memory, shared led system, high-speed access to data, high-speed network connecting compute nodes. • Cooperatively solving implies manual or
Matrix Multiplication using SUMMA and Canon CMPSC 450 Matrix Multiplication Exploded (CUDA?) *=*=*= *=*=*= *=*=*= CMPSC 450 SUMMA Step 1 *=*=*= *=*=*= *=*=*= Locally Owned A Locally Owned B Mult Input A (temp) Mult Input B (temp) Partial Locally Owned Answer (1/3) CMPSC 450 SUMMA Step 2 *=*=*= *=*=*= *=*=*= Locally Owned A Locally Owned
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CMPSC 450 Concurrent Scientific Programming Introduction CMPSC 450 Welcome to the class! • Class meets MWF 8-8:50AM on Zoom • Office hours • Tuesdays and Thursdays 8PM – 9PM. On Zoom. • By appointment • Email: use Canvas • About me: • Master of Engineering, CSE, Penn State 2001 • 20 years industry experience •
CPSC 425: Computer Vision Assignment 6: Deep Learning Attribution: This assignment is developed based on the example here. Preface This assignment consists of three parts: In the first part, you will implement various PyTorch deep learning layers using Numpy; in part two, you will experiment with different hyper-parameters on a image classification task and find
CS计算机代考程序代写 cuda GPU deep learning python CPSC 425: Computer Vision Read More »
18-646: How To Write Fast Code II (Spring 2021) Mini-Project 1 – Multicore Programming Due: Monday, April 12th at 11:59PM EST The goal of this project is to use your understanding of parallel computing resources in a manycore processor to optimize two fully functional applications. The applications are Matrix Multiple and K- Means Clustering. For
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License Computer Graphics Anatomy of the CUDA arrayMult Program: 2 #defines, #includes, and Globals mjb – March 27, 2021 Copyright By PowCoder代写 加微信 powcoder #include #include #include #include #include // CUDA runtime #include // Helper functions and utilities to work with CUDA #include “helper_functions.h”
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