---
geometry: margin=2cm
output: pdf_document
title: CSCI 5451 Assignment 1
date: \today

author: |
  | Michael Zhang \<zhan4854@umn.edu\> $\cdot$ ID: 5289259
---

1.  _A short description of how you went about parallelizing the classification algorithm. You should include how you decomposed the problem and why, i.e., what were the tasks being parallelized._

    The parallelization I used was incredibly simple, just parallelizing outer iterations. I used this same trick for both the OpenMP and the pthreads implementations.

    The reason I didn't go further was that further breaking down of the for loops incurred more overhead from managing the parallelization than was actually gained. I have run this several times and the gains were either neglient, or it actually ran slower than the serial version.

    This also had to do with the fact that I had already inlined most of the calculations to require as few loops as possible, moved all allocations to the top level, and arranged my data buffer in column-major order instead since the iteration pattern was by dimension rather than by row.

2.  _Timing results for 1, 2, 4, 8, and 16 threads for the classification. You should include results with outer iterations set to 10._

    ```
    ./lc_pthreads ./dataset/small_data.csv ./dataset/small_data.csv 10 1
    Program time (compute): 0.0069s
    ./lc_pthreads ./dataset/small_data.csv ./dataset/small_data.csv 10 2
    Program time (compute): 0.0027s
    ./lc_pthreads ./dataset/small_data.csv ./dataset/small_data.csv 10 4
    Program time (compute): 0.0027s
    ./lc_pthreads ./dataset/small_data.csv ./dataset/small_data.csv 10 8
    Program time (compute): 0.0033s
    ./lc_pthreads ./dataset/small_data.csv ./dataset/small_data.csv 10 16
    Program time (compute): 0.0031s
    ./lc_pthreads ./dataset/MNIST_data.csv ./dataset/MNIST_label.csv 10 1
    Program time (compute): 21.5287s
    ./lc_pthreads ./dataset/MNIST_data.csv ./dataset/MNIST_label.csv 10 2
    Program time (compute): 10.6175s
    ./lc_pthreads ./dataset/MNIST_data.csv ./dataset/MNIST_label.csv 10 4
    Program time (compute): 5.2198s
    ./lc_pthreads ./dataset/MNIST_data.csv ./dataset/MNIST_label.csv 10 8
    Program time (compute): 4.5690s
    ./lc_pthreads ./dataset/MNIST_data.csv ./dataset/MNIST_label.csv 10 16
    Program time (compute): 3.6433s
    ./lc_openmp ./dataset/small_data.csv ./dataset/small_data.csv 10 1
    Program time (compute): 0.0033s
    ./lc_openmp ./dataset/small_data.csv ./dataset/small_data.csv 10 2
    Program time (compute): 0.0017s
    ./lc_openmp ./dataset/small_data.csv ./dataset/small_data.csv 10 4
    Program time (compute): 0.0011s
    ./lc_openmp ./dataset/small_data.csv ./dataset/small_data.csv 10 8
    Program time (compute): 0.0020s
    ./lc_openmp ./dataset/small_data.csv ./dataset/small_data.csv 10 16
    Program time (compute): 0.0032s
    ./lc_openmp ./dataset/MNIST_data.csv ./dataset/MNIST_label.csv 10 1
    Program time (compute): 21.7196s
    ./lc_openmp ./dataset/MNIST_data.csv ./dataset/MNIST_label.csv 10 2
    Program time (compute): 10.4035s
    ./lc_openmp ./dataset/MNIST_data.csv ./dataset/MNIST_label.csv 10 4
    Program time (compute): 5.2449s
    ./lc_openmp ./dataset/MNIST_data.csv ./dataset/MNIST_label.csv 10 8
    Program time (compute): 4.1550s
    ./lc_openmp ./dataset/MNIST_data.csv ./dataset/MNIST_label.csv 10 16
    Program time (compute): 3.5328s
    ```

    This data was generated using the `run_benchmark.sh > out.txt` script.

Small note: There's a part in the end of the program that performs validation on the trained model by using a train/test data set split. I didn't count this towards execution time but felt that it was important enough to keep since it ensured that my program was still behaving correctly.

```

```