Code Monkey home page Code Monkey logo

Comments (2)

ctcyang avatar ctcyang commented on June 16, 2024

Thank you for your interest.

What --niter tells is how many times you want to compute PageRank to convergence _after warm-up. The default convergence criteria is whichever is first reached:

  1. 1e-8 (see
    float eps = 1e-8;
    ).
  2. PageRank iteration count reaches max_niter (see
    for (iter = 1; error > eps && iter <= desc->descriptor_.max_niter_; ++iter) {
    ).

If you set --timing 1 (error with the run_pr.sh script that only echoes --timing 1 but actually executes --timing 0), you should see a print out that looks as follows. Since my GPU is 1 generation older than yours, it took me 217.967ms to process 10 PageRank iterations. Then the per PageRank iteration would be 217.967ms / 10 iterations = ~21.8ms / iteration, which is close to the number in the paper.

$ bin/gpr --timing 1 --mxvmode 0 --niter 1 --max_niter 10 /mario-2TB/ctcyang/qe-dataset/soc-LiveJournal1/soc-LiveJournal1.mtx

Undirected due to mtx: 1
Undirected due to cmd: 0
Undirected: 1
Remove self-loop: 1
%%MatrixMarket matrix coordinate pattern symmetric
4847571 4847571 85702474
Allocate 4847572
Allocate 102842968
Allocate 102842968
Error: Unable to open file for writing!
Do not allocate 4847571 0x7fd188043010
Do not allocate 85702474 0x7fd08981e010
Do not allocate 85702474 0x7fd070fcd010
Do not allocate 4847571 0x7fd188043010
Do not allocate 85702474 0x7fd08981e010
Do not allocate 85702474 0x7fd070fcd010
output:
[0]:1.12354e-06 [1]:4.34784e-06 [2]:2.16458e-06 [3]:1.48264e-06 [4]:1.68473e-06 [5]:1.11411e-06 [6]:2.48564e-06 [7]:9.69221e-07 [8]:5.61167e-07 [9]:1.47378e-06 [10]:8.87791e-07 [11]:1.77316e-06 [12]:1.18192e-06 [13]:7.88482e-06 [14]:1.31274e-06 [15]:3.38896e-07 [16]:1.20574e-06 [17]:1.02075e-06 [18]:2.78271e-07 [19]:1.04159e-05 [20]:7.94688e-07 [21]:1.20331e-06 [22]:4.49042e-07 [23]:5.67421e-07 [24]:5.63578e-07 [25]:1.58316e-07 [26]:9.8955e-07 [27]:4.66949e-07 [28]:9.72953e-07 [29]:3.67839e-07 [30]:2.34166e-07 [31]:1.38741e-06 [32]:1.72217e-06 [33]:4.49905e-07 [34]:8.2128e-07 [35]:1.35088e-07 [36]:7.25688e-07 [37]:2.52794e-07 [38]:5.797e-07 [39]:9.27886e-07
CPU PR finished in 1873.186157 msec. Search depth is: 4. Resultant: 0.000000
1, 0.000985679/4847571, 4847570, pull, 22.6468
2, 0.000483457/4847571, 4847570, pull, 21.8343
3, 0.000184684/4847571, 4847570, pull, 21.8025
4, 0.00013746/4847571, 4847570, pull, 21.8063
5, 8.16702e-05/4847571, 4847570, pull, 21.7956
6, 6.52675e-05/4847571, 4847570, pull, 21.8284
7, 4.3504e-05/4847571, 4847570, pull, 21.8376
8, 3.55718e-05/4847571, 4847570, pull, 21.8678
9, 2.48263e-05/4847571, 4847570, pull, 21.8801
11, 2.05546e-05/4847571, 4847570, pull, 21.8526

CORRECT
1, 0.000985679/4847571, 4847570, pull, 21.8169
2, 0.000483457/4847571, 4847570, pull, 21.8275
3, 0.000184684/4847571, 4847570, pull, 21.8266
4, 0.00013746/4847571, 4847570, pull, 21.77
5, 8.16702e-05/4847571, 4847570, pull, 21.7376
6, 6.52675e-05/4847571, 4847570, pull, 21.7971
7, 4.3504e-05/4847571, 4847570, pull, 21.8248
8, 3.55718e-05/4847571, 4847570, pull, 21.8723
9, 2.48263e-05/4847571, 4847570, pull, 21.8034
11, 2.05546e-05/4847571, 4847570, pull, 21.8062
cpu, 1910.01,
warmup, 300.533, 0
tight, 217.967
vxm, 297.536

CORRECT

Another difference is I changed the header to make the graph be treated as a symmetric graph. In the paper, this is reflected Table 12 by an rs beside soc-LiveJournal1 (s for symmetric).

%%MatrixMarket matrix coordinate pattern symmetric
4847571 4847571 85702474

If you are a purist and want to treat the graph as directed, you can by passing in a --directed 1 flag. Running the graph as directed, runtime goes down to 18.8185ms / iteration.

from graphblast.

dkoutsou avatar dkoutsou commented on June 16, 2024

Thank you very much for your answer! Now one iteration on my GPU takes about 5ms. Makes much more sense!

from graphblast.

Related Issues (17)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.