Hi Alex,

I finally got to investigate the issue in depth. And there are two major
problems blocking your implementation from running the futures in parallel.

1) Allocations of boxed flonums. I tried to get rid of those by
allocating "scratchpad" flvectors and mapping everything onto them. The
future scheduling started to look different, however there are many
allocations because of your loops in functions cp3-futures and

I didn't finish the work though, because I noticed another strange
thing. The Typed Racket code in the lambda function returned by spline
(your mmax-fn argument) blocks almost entirely the parallel execution on
... type checks.

2) All those =, < and friends just block it.

So how to fix this? Well, it is relatively easy albeit quite a lot of
manual work.

(I am looking only at the cp3-futures function when talking about
possible improvements).

* Change the all the for loops for let loop forms and use preallocated
flvectors to hold all the values.
* Switch to racket/unsafe/ops for everything inside futures (this is not
necessary, but takes away a few possible surprises)
* Restructuralize the way you split the work into 30 futures and just
use a binary tree of futures as suggested earlier.
* Use racket/unsafe/ops from regular racket to implement the spline
interpolation. I would also move the coefficients into one huge flvector
and forgot about lists at all. This is very specific workload.

And do not worry about GCs. Once you get rid of all allocations inside
futures, the GCs will disappear.

Also bear in mind that my suggestions are rather low level. By following
them you will get the algorithm to scale over multiple cores if you
really need it. Just remember it will be at a huge cost to readability.
You can slightly mitigate this by some refactoring and custom syntax,
but that is even more work and I would really consider whether you need
the parallelism for a computation that takes a few seconds anyway.

Of course, if you plan to use your algorithm for much bigger data set,
this is the way to go (including the custom syntax).


On 17. 06. 20 10:50, Alex Harsanyi wrote:
> I am trying to speed up an algorithm using futures, but I am getting
> some unexpected results (and no real speed improvements), and I was
> wondering if someone more experienced could have a look a the code and
> tell me what am I doing wrong.
> I put up the code in this repository:
> https://github.com/alex-hhh/cp3-exeriments, unfortunately it is the
> simplest meaningful example that I can come up with.  Most of the
> functions, however are just support functions and there are six
> implementation of the same algorithm.
> Basically, the problem I am trying to solve is to fit a model to
> existing data and this is done by evaluating 2.5 million combinations of
> parameters.  My best, non-futures based, algorithm can do this in about
> 3 seconds (8 seconds in DrRacket).
> Given that each of this 2.5 million combination is completely
> independent from the others, they could all be done in parallel.  Given
> this, I "sliced" the combinations into 30 groups and tried to perform
> each "slice" in its own future and select the best among the 30 results
> produced by these futures.
> Unfortunately, while the futures versions of the algorithm produce the
> correct result, the algorithm runs at the same speed as the non-futures
> version.  My `processor-count` returns 8, so I would expect at least
> some level of parallelism.
> As a first step, I tried using `would-be-future`, to see if it reported
> any operations which might block, but nothing was printed out.
> I also tried using the futures visualized, and I found the following:
> * the code appears to be blocking on primitive operations, such as +, -,
> < etc.
> * I suspect these operations are inside the code generated by the `for`
> loops, so I am not sure how to remove them without making the code even
> more difficult to read.
> * there seems to be a lot more time spent in the garbage collector when
> running the futures visualizer than without it (DrRacket runs with
> unlimited memory)
> So I am wondering if someone who is more familiar with futures can look
> at the code and provide some hints about what can be done to make this
> code run in parallel (or if it cannot, I would like to understand why).
> This is already a long message, so I will not add further details here,
> but the repository at https://github.com/alex-hhh/cp3-exeriments has an
> explanation of what every function does, and I am happy to provide
> further clarifications if needed.
> Thanks,
> Alex.
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