What is MLC@Home?

MLC@Home is a distributed computing project dedicated to understanding and interpreting complex machine learning models, with an emphasis on neural networks. It uses the BOINC distributed computing platform. You can find more information on our main website here: https://www.mlcathome.org.

Neural Networks have fuelled a machine learning revolution over the past decade that has led to machines accomplishing amazingly complex tasks. However, these models are largly black boxes: we know they work, but they are so complex (up to hundreds of millions of parameters!) that we struggle to understand the limits of such systems. Yet understanding networks becomes extremely important as networks are deployed in safety critical fields, like medicine and autonomous vehicles.

MLC@Home provides an open, collaborative platform for researchers studying machine learning comprehension. It allows us to train thousands of networks in parallel, with tightly controlled inputs, hyperparameters, and network structures. We use this to gain insights into these complex models.

We ask for volunteers to donate some of their background computing time to help us continue our research. We use the time-tested BOINC distributed computing infrastructure — the same infrastructure that powers SETI@home's search for alien life, and Rosetta@home's search for effective medications. BOINC is fun — you get credit for each bit of compute that you do, with leaderboards and milestones. All while helping further open research. Please follow the link below to join, and happy crunching!

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News

[TWIM Notes] Oct 19 2020 posted
MLC@Home has posted the Oct 19, 2020 edition of its weekly "This Week In MLC@Home" newsletter! Brief updated on GPU support, Dataset 4, OSX support and more.

Read it and join the discussion here.
20 Oct 2020, 3:34:29 UTC · Discuss


[TWIM Notes] Oct 19 2020
This Week in MLC@Home
Notes for Oct 19 2020
A weekly summary of news and notes for MLC@Home

Summary
A quick summary this week, as it was a quiet week on the forums and busy week outside of the project. Hey, sometimes life happens. See below for GPU support updates, Paper updates, Dataset 4, and OSX support.

News:


  • We've completed the first Dataset 3 milestone! Well done all our volunteers! The next steps are to package it up, and write up a brief analysis/paper to submit to arXiv and release the dataset to the public! Milestone 2 (1000x100) work underway!
  • We spent some time last week gaining access to both Windows and Linux machines with CUDA, so hoepfully GPU clients should be released to testing this week. We're having some issues packaging the ROCm version but will try to iron those out into testing as well.
  • We also secured access on an OSX machine, and have run the client on OSX! However, packaging on OSX faces another set of similar challenges to ROCM packaging up the libraries with the
  • Dataset 4 preparations continues. We have the data, just need some backend updates to updates to handle the new type or networks (classification vs. regression).
  • No changes to Dataset 1+2 yet, there are some updated Partiy and EightBit WUs in testing, but we have not processed those results yet to make certain they're set for full release.



Project status snapshot:
(note these numbers are approximations)

Tasks
Tasks ready to send 25261
Tasks in progress 21240
Users
With credit 961
Registered in past 24 hours 45
Hosts
With recent credit 2064
Registered in past 24 hours 15
Current GigaFLOPS 248734.27

Dataset 1 and 2 progress:

SingleDirectMachine      10002/10004
EightBitMachine          10001/10006
SingleInvertMachine      10001/10003
SimpleXORMachine         10000/10002
ParityMachine              854/10005

ParityModified             243/10005
EightBitModified          6365/10006
SimpleXORModified        10005/10005
SingleDirectModified     10004/10004
SingleInvertModified     10002/10002 

Dataset 3 progress:
Overall (so far): 26430/30112
Milestone 1, 100x100:  10000/10000
Milestone 2, 100x1000: 26430/100000
Milestone 3: 100x10000: 26430/1000000


Last week's TWIM Notes: Oct 12 2020

Thanks again to all our volunteers!

-- The MLC@Home Admins
20 Oct 2020, 3:32:06 UTC · Discuss

[TWIM Notes] Oct 12 2020 posted
MLC@Home has posted the Oct 12, 2020 edition of its weekly "This Week In MLC@Home" newsletter! 100 days, a new server, and other progress updates.

Read it and join the discussion here.
13 Oct 2020, 2:55:17 UTC · Discuss


[TWIM Notes] Oct 12 2020
This Week in MLC@Home
Notes for Oct 12 2020
A weekly summary of news and notes for MLC@Home

Summary
Happy 100 days, MLC@Home! On October 8th, MLC@Home passed 100 days old as a project, and early adopter badges were added to everyone with credit at that point. Thanks again for all your support.

Beyond that, we transitioned to our new server, which is quite a step up from the old one, and puts us in good shape for Dataset 3+4 validation and beyond. Read on for more information.

News:


  • Dataset 3 WUs processing going fantastically, but a few stragglers remain before we hit the first milestone (100x100). New WUs have been released towards the next milestone (100x1000). We'll continue to trickle them out about 500 at a time, and update the scoreboard to keep track.
  • We studied the the runtimes of dataset 3 WUs, and decided to increase the credit awarded for all new WUs. There are still old WUs in the pipeline that have the old credit value, and will take a while for those time finish, but new ones created will have more credit.
  • We're testing a new, longer set of Dataset1+2 WUs in the mldstest application, with a longer runtime and a corresponding change in credit awarded. Datasets 1+2 continue also to make progress in parallel with Dataset 3.
  • New server up and running. Thanks for your patience. There may need to be another quick downtime (15 minutes) to swap a disk around insice the machine, but otherwise its been running fine since Saturday afternoon.
  • Old credit should be counted towards badges now!
  • This doesn't effect anyone here, but the FLOPS estimate for dataset 3 is grossly underspecified (which is why the "GFLOPS" estimate below is so much lower than usual). We'll fix that in future WUs. It doesn't matter for users, but it helps convince other researchers if I can quote a (more) accurate GFLOPS estimate..
  • Next up (in vague priority order): GPU support, Dataset 4, Dataset Release Paper writing, OSX support.



Project status snapshot:
(note these numbers are approximations)

Tasks
Tasks ready to send 41238
Tasks in progress 21350
Users
With credit 910
Registered in past 24 hours 47
Hosts
With recent credit 2029
Registered in past 24 hours 58
Current GigaFLOPS 24544.93

Dataset 1 and 2 progress:

SingleDirectMachine      10002/10004
EightBitMachine          10001/10006
SingleInvertMachine      10001/10003
SimpleXORMachine         10000/10002
ParityMachine              804/10005

ParityModified             218/10005
EightBitModified          6221/10006
SimpleXORModified        10005/10005
SingleDirectModified     10004/10004
SingleInvertModified     10002/10002 

Dataset 3 progress:
Overall (so far): 17197/30112
Milestone 1, 100x100:  9975/10000
Milestone 2, 100x1000: 17197/100000
Milestone 3: 100x10000: 17197/1000000


Last week's TWIM Notes: Oct 5 2020

Thanks again to all our volunteers!

-- The MLC@Home Admins
13 Oct 2020, 2:50:02 UTC · Discuss

Scheduled Server Maintenance
MLC@Home will be going down at midnight (Easter US timezone) tonight, Oct 8th (a little over 4 hours from now), to migrate to a new, more powerful server.

The outage is scheduled for all day Oct 9th, during which time the web site and boinc work schedulers will be offline. We expect to be back up and running (on a much more powerful server!) by the morning of Oct 10th (hopefully sooner!). We'll post updates to twitter with progress in case something doesn't go according to plan: https://twitter.com/MLCHome2 .

Thanks again for your support, and we'll be back shortly!
9 Oct 2020, 23:24:44 UTC · Discuss


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©2020 MLC@Home Team
A project of the Cognition, Robotics, and Learning (CORAL) Lab at the University of Maryland, Baltimore County (UMBC)