[SOLVED] ME 759 - Assignment 4

Description

High Performance for Engineering Applications

All commands or code must work on Euler with only the cuda module loaded unless specified otherwise. Commands and/or code may behave differently on your computer.

. Consider using a formatter like clang-format.

* Before you begin, copy the provided files from HW04 of the ME759-2020 repo. Do not change any of the provided files because we will write clean copies over them .

1. (a) Implement in a file called matmul.cu the matmul and matmul kernel functions as declared and described in matmul.cuh.

• Write a program cu which does the following:
  • Creates matrices (as 1D row major arrays) A and B of size n*n in managed (aka unified) memory.
  • Fills those matrices however you like.
  • Calls your matmul
  • Prints the last element of the resulting matrix.
  • Prints the time taken to perform the multiplication in milliseconds using CUDA events.
  • Compile: nvcc task1.cu matmul.cu -Xcompiler -O3 -Xcompiler -Wall -Xptxas -O3 -o task1
  • Run (where n and threads per block are positive integers): ./task1 n threads per block
  • Example expected output:

11.36

1.23

• On an Euler compute node, run task1 for each value n = 2⁵,2⁶,·· ,2¹⁵ and generate a plot task1.pdf which plots the time taken by your algorithm as a function of n when threads per block = 1024. Overlay another plot which plots the same relationship with a different choice of threads per block.

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2. (a) Implement in a file called stencil.cu stencil and stencil kernel functions as declared and described in stencil.cuh. These functions should produce the 1D convolution of image and mask:

R output[i] = ^X image[i + j] ∗ mask[j + R] i = 0,··· ,n − 1

j=−R

Assume that image[i] = 0 when i < 0 or i > n − 1. Pay close attention to what data you are asked to store and compute in shared memory.

• Write a program cu which does the following:
  • Creates arrays image (length n), output (length n), and mask (length 2 * R + 1) all in managed memory.
  • Fills those arrays however you like.
  • Calls your stencil
  • Prints the last element of the resulting array.
  • Prints the time taken to perform the convolution in milliseconds using CUDA events.
  • Compile: nvcc task2.cu stencil.cu -Xcompiler -O3 -Xcompiler -Wall -Xptxas -O3 -o task2
  • Run (where n, R, and threads per block are positive integers):

./task2 n R threads per block

• Example expected output:

11.36

1.23

• On an Euler compute node, run task2 for each value n = 2¹⁰,2¹¹,·· ,2³¹ and generate a plot task2.pdf which plots the time taken by your algorithm as a function of n when threads per block = 1024 and R = 128. Overlay another plot which plots the same relationship with a different choice of threads per block.

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