Monday November 13th

Hotswapping Haskell and Probabilistic Programming

Jon Coens gave a talk on Haxl’s GHC Linker system. These are notes based on a presentation he gave at Haskell Hackers
He comes from a systems engineering background, which I thought was pretty sweet, since that’s what I was interviewing for on Friday, even though I had no idea what it was :)

should be able to suck in code the same way a bytestring or text is sucked in
Hotswapping shared objects .so or .dll where new version of binary is swapped with old one
reference repo
Here is sort of a rough diagram of how it is visualized

dynamic linking : he used an example of taking every instance of “foo” and replacing in binary an object that represents the function you named “foo” in your function
Types: describes boundary between main binary and shared object

see line 152

unless resolved $ do
    unloadObj newSO
    throwIO (ErrorCall $ "Unable to resolve 
    objects for " ++ newSO)

c_sym <- lookupSymbol symName
  h <- case c_sym of
    Nothing -> do

assuming all resolved, can pull symbols out
purge vs unload- keep libraries but forget symbols you know about. This is so that when a new instance is called, it doesn’t conflict with old symbols
updateState… line 118

updateState mvar symbolName nextPath = do
  newVal <- force <$> l
  oadNewSO symbolName nextPath
  -- Build a new state for this version

cross-boundary inlining (I need to look this up. I know what function inlining is)
flag..keep haskell code in binary

I had seen his talk at Compose Conference, so was interesting to see how he adapted it for more business-oriented audience (he was using us as his test audience for a presentation he had to give internally the next morning)
Supply chain optimization is stochastic
Target has 87 stores to be supplied by 37 supply centres
Their job is to minimize total inventory while supplying stores. Thinking about things like spoilage, while keeping inventory on shelves.

We don’t know what will sell, if any
Probability Distributions needed
- sampling simulations (useful for where small sample size needed)
- exhaustive (where entire distribution is needed). Useful for applying domain-specific algorithms where specific data is needed

So a probability is a map from a -> b
Therefore, distributions form a functor
A die can be thought of a boolean operation
If we take odds as 1 and evens as 0, we can map the value to a coin
However, it becomes difficult to reverse this, as we lack information (two values to represent six). How then, do we add the “noise” back? He referenced a monadic bind operator

We have two dice
We can take all the probabilities possible and then flatten them
We can also take a biased set of coins, for example, one that gives a probability of .1 for heads and .9 for tails and create with two of them, a tree of all possibilities. We can also then flatten or simplify that tree into just heads or tails
He also discussed join and flat map with similar analogies

This is not viable for long scaling of applications. When you flatten a probability graph, it may not accurately represent probability distribution
there are models that are say, quadratic, that don’t fit
there are languages with randomness built into them

We went out to Firehouse afterwards for food and drinks!
I had about seven minutes between the time Caltrain arrived and the time I caught my bus back at San Jose Diridon. Tikhon was nice enough to keep an eye on the time for me. I also met Nick, from my FP Slack. He said he probably wouldn’t have even made it if I didn’t tell him about the Meetup. That was really nice of him! I had a blast, and man, the company was just wonderful! Left the Meetup with a smile on my face, and lots to think about!

I’m going to this Recruitment event tomorrow, or if not, my sailing Monthly meeting. It’s an invite-only event, so we’ll see.
Have to work on C++ game. Ben (from my Haskell group) was really nice and said if I needed any assistance, to feel free to contact him! Means a lot; he’s awesome at C++, and I like getting beaten up by C++, and keep coming back for more! :)
C++ exam…wrote up cheat sheet today (I need more practice on Operator overloading).
Have to work on Google / Udacity coursework. My internet was a bit down today, but it’s back up, so….good timing
Also, I finished my resume for this application that had very specific requirements. It was my first time writing an academic resume. Man, they have different interests. They care more about things like Publications and Presentations, which is interesting. I don’t have much of that, but hey, it’s something I can work on in the future! Right now, I’d like the opportunity and I’d like to continue coding. It’s the one thing I’d love to do for the rest of my life. I just have to get a professor recommendation and submit (fingers crossed).

Written on November 13, 2017