On 08/27/2012 09:11 AM, Vincent St-Amour wrote:
TR's complex number optimizations eliminate repeated boxing and unboxing
in chains of operations that each consume and produce complex numbers.
Similar optimizations for structs would eliminate structs for
intermediate results in chains of operations that each consume and
produce that same (single) kind of struct.
If your code has such chains of operations, then these optimizations
could apply.
Do you have code that you think would benefit that I could look at?
Not yet. I've given up on a union of different probability
representation types for now.
For arrays, I could. An array is just a function with a finite,
rectangular domain (a "shape"). Think of the type like this:
(struct: (A) array ([shape : (Vectorof Index)]
[proc : ((Vectorof Index) -> A)]))
(This is a bit simplified.) So
(array-exp (array-abs arr))
doesn't actually compute (log (abs x)) for any `x', it just creates an
array that would if you asked it for an element. IOW, it's equivalent to
(array-map (compose exp abs) arr)
which itself is equivalent to
(array (array-shape arr) (compose exp abs (array-proc arr)))
If I made functions like `array-exp' and `array-map' into macros, and if
array structs were unboxed, Racket's optimizer could inline the
compositions. I imagine this eventual lovely outcome:
(let ([proc (array-proc arr)])
(array (array-shape arr)
(lambda (x) (unsafe-flexp (unsafe-flabs (proc x))))))
There are also FlArray and FCArray, which are subtypes of Array that
store their elements (unboxed in flvectors and fcvectors).
FlArray-specific operations are currently about 5x faster than Array's.
But Array's ops don't allocate stores for intermediate results, so with
the right optimizations, Array's could be the faster ones.
If you want to have a look right now, checkout
https://github.com/ntoronto/racket.git
and try this program:
#lang typed/racket
(require math/array)
(define arr (array [[1.2 4.0] [3.2 -1.8]]))
(inline-array-map exp (inline-array-map abs arr))
Neil ⊥
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