GPU610/Team AGC
Team AGC
Team Members
- Andy Cooc, Some responsibility
- Gabriel Castro, Some other responsibility
- Christopher Markieta, Some other responsibility
Progress
Assignment 1
Andy's Findings
...
Gabriel's Findings
Pillow Library (Python)
The Pillow library is an image manipulation library for python. It has many common functions like re-sizing, cropping, rotating, blur, sharpen etc. It's available on github at https://github.com/python-pillow/Pillow
I used 4 filters for testing
filter | run time |
---|---|
Blur | 1.305s |
Gaussian Blur | 4.492 |
Auto Contrast | 0.092 |
Grey Scale | 0.046 |
See the code on github.
Gaussian Blur
A gaussian blur is a filter that can be applied to an image to make it blurry, in its simplest form it goes through every pixel in an image and averages it with its surrounding pixels. In the Pillow library it is implemented in a C module. This helps with processing time as C is hundreds of times faster than python. A quick look at the source shows that algorithm contains a nested for loop that's O(x * y) and then one that's O(x * y * r), that means that time grows n^2 based on the size of the image and n^3 based on the size of the blur radius.
Conclusion
With many nested operations, this a really good candidate for GPU paralization.
Christopher's Findings
xor_me
xor_me is an open source, brute force password cracker for doc and xls files.
xor_me was written by Benoît Sibaud and is copyrighted under the terms of the GNU Lesser General Public License version 3 only, as published by the Free Software Foundation. Here is a link to my fork of this repository:
https://github.com/Markieta/xor_me
Here is the profile of a short run of brute_force:
Flat profile: Each sample counts as 0.01 seconds. % cumulative self self total time seconds seconds calls Ts/call Ts/call name 99.35 10.58 10.58 lclGetKey(unsigned char const*, long) 0.19 10.60 0.02 dump_exit(int) 0.00 10.60 0.00 1 0.00 0.00 _GLOBAL__sub_I__Z9lclGetKeyPKhl
As you can see, lclGetKey is the function where I will spend most of my time trying to parallelize code.
This application is quite CPU intensive, but hasn't been optimized for multiple threads. It is using 100% of 1 thread from the 8 available on my CPU. See the list of processes below for an example.
top - 23:25:32 up 1:16, 3 users, load average: 0.94, 0.65, 0.60 Tasks: 256 total, 2 running, 253 sleeping, 0 stopped, 1 zombie %Cpu(s): 13.7 us, 0.7 sy, 0.0 ni, 85.5 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st KiB Mem: 3979012 total, 3270196 used, 708816 free, 352592 buffers KiB Swap: 4124668 total, 0 used, 4124668 free. 984048 cached Mem PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 5229 markieta 20 0 12664 1064 896 R 100.0 0.0 1:06.04 brute_force 1467 root 20 0 538620 208272 166664 S 3.7 5.2 6:55.85 Xorg 2540 markieta 20 0 1084328 169500 53460 S 3.3 4.3 11:57.88 chrome 2075 markieta 9 -11 509016 6840 4500 S 2.7 0.2 3:21.47 pulseaudio 3022 markieta 20 0 1094124 79252 10220 S 2.3 2.0 3:05.77 chrome 2932 markieta 20 0 829212 43176 19848 S 1.7 1.1 0:31.29 /usr/bin/termin 2989 markieta 20 0 1039100 117292 23968 S 1.7 2.9 1:48.53 chrome 2296 markieta 20 0 1553220 170248 65592 S 1.0 4.3 3:16.43 compiz 2789 markieta 20 0 1064160 99040 20116 S 0.7 2.5 1:24.61 chrome 2993 markieta 20 0 1112596 155316 26192 S 0.7 3.9 1:31.43 chrome 3482 root 20 0 0 0 0 S 0.3 0.0 0:07.34 kworker/2:2 4364 root 20 0 0 0 0 S 0.3 0.0 0:00.96 kworker/0:0 5230 markieta 20 0 24952 1776 1176 R 0.3 0.0 0:00.14 top
Here I ran the brute_force function again to see how long it would really take. I did not run this command for too long, hence the the termination ^C
after about 2 minutes.
markieta@Y560:~/Documents/xor_me$ time ./brute_force 0x499a 0xcc61 Key: 499a Hash: cc61 Password: '1950' Password: 'w2#1' ^CState: 20:22:48:46:7e:48:62:c3c0:00000184023807d008a011c010800000:6c62477d45472100 real 2m16.888s user 2m16.082s sys 0m0.640s
I am hoping to see a lot of improvement after my research and implementation with CUDA and OpenCL.
Team AGC has decided to collaborate on this project for assignment 2 onwards.
Assignment 2
Christopher's Findings
xor_me
Since the majority of CPU cycles is spent in the most inner for-loop, the goal is to parallelize this code only. It is possible to parallelize all 8 for-loops (Maximum of 8 character password) because they are performing very similar tasks. However, due to the time constraint and purpose of this assignment, I will only focus on this one. See below for the following code to be optimized for our GPU:
for (o=32; o < 128; ++o) { skipInits: unsigned short x = nHash ^ hash; lclRotateRight(x, 1); if (32 <= x && x < 127) { t[0] = static_cast<unsigned char>(x); if (nKey == lclGetKey(t, 16)) { std::cout << "Password: '" << t << "'" << std::endl; } } hash ^= r[1]; r[1] = t[1] = o; lclRotateLeft(r[1], 2); hash ^= r[1]; if (o == 32) { r[0] = '\0'; hash = lclGetHash(t, r, 16); } }
At first it seems impossible to do because of the data dependencies: hash, r[1], t[1], and o. But after doing some research, I have learned that the XOR operation is communicative and associative, meaning that we can simply calculate all of the dependencies in parallel first, then combine the results to achieve the same data.
Here is a non-formal proof to help make my point clear. The ability to achieve the same result vertically and horizontally will be the key to solving this task.
Step 1: 101 ^ 001 ^ 111 = 001 111 ^ 100 ^ 001 = 010 100 ^ 010 ^ 001 = 111 || || || 110 111 111 Step 2: Operate with vertical and horizontal 001 ^ 010 ^ 111 = 110 110 ^ 111 ^ 111 = 110