Difference between revisions of "Meeting 01-07-2013"
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==== Present ==== | ==== Present ==== | ||
− | SH, SC, JP, JB, Adam (Experience student) | + | [[SH]], [[SC]], [[JP]], [[JB]], Adam (Experience student) |
== Overview == | == Overview == | ||
− | SC presented a flow diagram of Compiler <--> MAGEEC <--> ML and what data is generated and exchanged where, and what the flow is. Will be on wiki. | + | SC presented a flow diagram of [[Interface_Flow|Compiler <--> MAGEEC <--> ML]] and what data is generated and exchanged where, and what the flow is. Will be on wiki. |
== Definition of features == | == Definition of features == | ||
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* [[JB]] Flag up with Tom Harris that the ~30% Q1-Q4 UoB staff budget will be rolled forward | * [[JB]] Flag up with Tom Harris that the ~30% Q1-Q4 UoB staff budget will be rolled forward | ||
* [[KIE]] To decide on whether for two PCs with 32GB was one PC with two cores and much more RAM | * [[KIE]] To decide on whether for two PCs with 32GB was one PC with two cores and much more RAM | ||
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+ | [[Category:Meetings]] |
Latest revision as of 10:20, 23 July 2013
Contents
Present
SH, SC, JP, JB, Adam (Experience student)
Overview
SC presented a flow diagram of Compiler <--> MAGEEC <--> ML and what data is generated and exchanged where, and what the flow is. Will be on wiki.
Definition of features
- Feature vectors need defining external to any compiler IR.
- Some compilers may or may not have some features available.
- The ML will need to ?regenerate? its data-sets for each option.
- Define 'essential' + 'optional' features?
- The feature vector needs to be defined.
- MILEPOST vector is a starting point, but some features may not be useful.
- Check with MILEPOST results.
- Discarding features could speed the flow.
- Are there language-specific features that are not so useful/a problem for future expandability?
Pass runs
- Need to run sets of passes in one go, not just a single pass in one go.
- Need to run lists of passes
- How to bound the number sensibly
- Some passes need to run multiple times (even after each other)
- Can ML predict how many passes needed before starting?
ML predictor requirements
- Takes in the current feature vector from a program with current passes run.
- Needs to return back a list of passes to run next (with goodness metrics?)
ML Training
- Probably use a separate application to do the training.
- Need to generate sets of flags (randomly?) based on the constraints of pass ordering (shared data structure from the prediction phase)
- Ordering of passes is important; can make a big difference in some cases.
Actions
- SC Begin initial write of compiler->MAGEEC interfaces. Dummy ML placeholder for now.
- SC Add list of upcoming meetings to wiki
- SH Ensure that next meeting includes all ML people to get feedback into that aspect.
- SH Apply for BlueCrystal Accounts for all
- SH Inform all about quarterly meetings
- SH Mailing list activation
- MG Begin on defining the feature vectors to be used, based on MILEPOST.
- JB Flag up with Tom Harris that the ~30% Q1-Q4 UoB staff budget will be rolled forward
- KIE To decide on whether for two PCs with 32GB was one PC with two cores and much more RAM