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Paolo:
we have submitted FWPs for LBL and FNAL (includes CalTech). We should receive all funds we asked for in our proposal in a single payment in FY16 (two weeks left).
Early “technical” goals:
Name the project - currently x-cut-hep-tracking : (MS suggestion) HEP-TrkX or HEP.TrkX (X standing for exploration and cross-cut!) 23.09.2016
Common sw repository - currently bitbucket → Maria to have a look and make a proposal -- Created repository https://github.com/cmscaltech/HEP.TrkX
(MS) Need everyone’s git account userid to add you
Shared dropbox/cernbox - currently google drive
Caltech box (MS) made an are in Box (50GB) and added Paolo to test how this works
Prabhat: also for data?
Good question, would work up to small sizes. Also we need to address data curation (see our proposal).
→ Jim K to propose solution for data
Project web page. Volunteers?
→ Maria undergrad will look into this
(MS) Will have the web page ready this weekend
Shared platform to run our codes?
Like lxplus, NERSC?(would need to apply for time this weekend), …
Prabhat recommends that Paolo put in an ERCAP allocation
1M core hours on Cori Phase II and/or Edison
Call out DOE grant and sponsoring PM
Call out that you will utilize NERSC production ML/DL libraries
Prabhat: What software frameworks is the team planning on using? (Theano, Caffe, TensorFlow, CNTK, Torch)
Crucial point.
Also having the ability to scale-up to big learning apps is crucial
Suggest to put in a small NERSC ERCAP request this weekend.
Maria: helped Brazilian group setup early-access to Intel tools. Wonder if it is the same access NERSC has. (the “Early Adopter Program” to receive servers with advanced tech) -- In negotiation to find out more about this deal soon
Maria is preparing a system with 16 GTx1080 on SuperMicro servers-- ready in Oct and for SC16 (MS)
Two/three days before the end of the year
Proposed dates, not yet vetoed:
After CHEP: Oct 17-19 (@LBL?)
Tue afternoon?
Wed afternoon during visit workshop
Before/after SC16(Nov 12-18),
Thursday 17 - Friday 18?
Standalone (Caltech offered to host, FNAL would prefer to host).
(http://dolcit.cms.caltech.edu/scmls/ another ML workhosp at Caltech, Nov 18)
Some weeks that should work for Paolo:
Oct 17
Oct 24
Nov 4-5 @ Caltech would for Maria, may help with travel restrictions.
Also at Fermi
Nov 7 (I don’t get to vote…NOOOOO)
Nov 28
Dec 5 (if need be)
Dec 12 (too late)
JBK cannot do Nov 4-5, Nov 1-3 works, FNAL would be a great place for the workshop (MS lets do it at FNAL Nov 1-3!)
Goals:
Get to know the team!
Review/update long-term goals listed in proposal also in view of reviewers feedback (when we get it!)
Define short-term goals (three-six months) in some detail. Probably include:
Generate both toy and “realistic” HL-LHC tracking data samples
Put together baseline and/or “state-of-the-art” solution(s) for seeding and tracking
Both could rely on aCTS infrastructure
Agree on quality metrics
Start experimenting with several ML techniques on toy samples.
Possible presentations/publications
Agree on software process (code management, testing, issue management)
Hackathons/teach-ins. For example:
aCTS simulation
Parallel CKF
NN training and testing with tensorflow (caffe, theano, you name it...)
Invite external collaborators (PCKF, aCTS)
Steve:
ACTS workflow setup for producing track data of varying complexity (e.g., no mag field, fewer layers) in order to explore limitations of our RNN models
Mayur:
Fitting LSTMs to tracks that are 1-Dimensional before moving on to 3D (LHC) data
Generating various trajectories as shown below
Understanding LSTM mechanics, limitations and features
Mayur will link his working document on this
Prabhat: is there LSTM expertise in our group
Maria: Jean Roch and students have done a project with LSTMs this summer.
Jim: mostly with summer students, using RNNs for signal processing.
Maria: Caltech will start in October. Will meet with Pietro and other to coord Caltech activities/situation. MS Have not met with Pietro and Yisong yet bc of DOE matters this week
Jim K: met with Lindsay and Giuseppe last week
Other news from Caltech (09.23.2016): one of MS grad students, Dustin Anderson has decided to become a data scientist after graduation. He is at CERN and will get back to Caltech in Dec. He will start spending time on ML and he has already done some v serious technical work on setting up distributive NPI architecture with JR (who spoke with Jim abotu this). I foresee engagement in our project. Also Javier Duarte (former student who just defended) has started as Lederman Fellow at FNAl and he is terrific -- we discussed he would join from FNAL side. On the side of Caltech I some have administrative issues but Panagiotis is helping.