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Project Meeting 2020.11.24
Ben Stabler edited this page Nov 24, 2020
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- Update from Jeff Doyle on TVPB multiprocessing/performance, see working example
- Running multiprocessed all the way through now on Mac
- Performance testing mostly linear - ~16 min 1 process, ~8 min 2 process, ~4 min 4 process
- Fixing a waiting for other processes to complete issue on Windows
- Adding chunking to initialize_tvpb as well to better manage memory
- We will review timing statements once we have the full scale Windows example run
- During model development, probably want to use dynamic calcs since operating on a small sample, but during application, probably want to use static/pre-compute calcs to save runtime
- Could probably speed up best path calc method even more if we spend more time on it
- Feature is important to SANDAG, MTC, ODOT so faster the better
- Let's get the full scale Windows run working, review timing statements, and discuss next steps
- @Jeff fix issue and then work on estimation mode and then I'll re-run
- Update from Jeff Newman on interaction_simulate estimation recipe and notebook example for larch, see issue
- Non-mand tour freq notebook done
- Like last time, instability in results since sample size is very small
- Added optional ability to link coefficients (with the exact same value) for estimation
- Run all feature working as well
- Maybe want to do a coefficient template across person types (like we did for mode choice)?
- @Doyle to update EDB for all person types and clean-up the CDAP coefficients as well so Newman can finish that too
- @Newman and Doyle to chat later this week
- Update from Clint on ARC progress
- Multiprocessed full scale model run runs in about 16 hours
- Using something like 36 of 40 processors on machine
- Trip scheduling went from 20 hours to 4 minutes with tidying up the code, filtering out choosers not needed, etc.
- This includes 5 iterations of work and school location choice shadow pricing
- Mandatory tour scheduling is the slowest module at 7 hours. Uses 30 minute time periods and logsums. Could be sped up a pre-processor, which ARC may do in the next round of work
- WSP just about done; plans to tidy up, write a verification memo, and then hand back to ARC
- ARC planning transition in mid/late 2021
- Great to see the same code base working for MTC, SEMCOG, and ARC. That's the mission of ActivitySim.
- Update from me on work_at_home model integration based on discussion with Mark
- DaySim has it as an oddball always available alternative in work location, rather than sampled
- Makes shadow pricing and estimation complicated
- Better for parcel level modeling since work_at_home means home, whereas for maz level modeling, people could work in the same maz but not work_at_home
- Best to split these models out, including storing results in separate person variables - work_at_home = T/F, work_zone = XXXXX
- The decision is then either before with simpler accessibility term or after with mode choice logsum
- Let's do after since SEMCOG wants to use the mode choice logsum and its a more complete measure
- The person work_at_home and telecommute_frequency attributes can be added to any downstream model without any code changes
- Can we sensitivity test the simpler accessibility term versus the mode choice logsum?
- Mode choice logsum will already be calculated so doesn't add much runtime to run the model after
- I'll update the spec and then we can get started on programming
- SANDAG talking with Boston MPO and DC MPO about telecommute modeling post COVID