Is there a reason we can't change the way unions of small bits types are represented, so that if we know something is a Union(Float64,NA) it can live in registers or on the stack instead of having to be heap allocated?
On Friday, August 1, 2014 2:54:49 PM UTC-4, Jameson wrote: > > I could (and probably will, someday) revive that commit. At the time, > though, I seemed to find that it provided little performance benefit -- the > gc cost of allocating boxes was far greater (for type uncertainty involving > bitstypes) and the type dispatch wasn't as much of a performance impact as > I had previously assumed. > > > On Friday, August 1, 2014, Keno Fischer <[email protected] > <javascript:>> wrote: > >> It is possible to do generic compiler improvements for Union types >> (Jameson had a branch at some point that did callsite splitting if we >> inferred a Union type). However, I think the best way to go here is to >> maintain the current separation of two arrays (one of the values one >> for the NAs), but give an option type on access. The option type would >> then most likely be in memory and wouldn't have much overhead. Please >> let me know if there's anything specific I should explain how the >> compiler will handle it, I admit I have only skimmed this thread. >> >> On Fri, Aug 1, 2014 at 9:18 AM, Simon Kornblith <[email protected]> >> wrote: >> > On Friday, August 1, 2014 6:23:59 AM UTC-4, Milan Bouchet-Valat wrote: >> >> >> >> Le jeudi 31 juillet 2014 à 21:19 -0700, John Myles White a écrit : >> >> >> >> To address Simon’s general points, which are really good reasons to >> avoid >> >> jumping on the Option{T} bandwagon too soon: >> >> >> >> >> >> >> >> * I agree that most languages use tagged union types for Option{T} >> rather >> >> than a wrapper type that contains a Boolean value. It’s also totally >> true >> >> that many compilers are able to make those constructs more efficient >> than >> >> Julia currently does. But what we should expect from Julia in the >> coming >> >> years isn’t so clear to me. (And I personally think we need to settle >> on a >> >> solution for representing missing data that’s viable in a year rather >> than >> >> viable in five years.) This is an issue that I’d really like to have >> input >> >> on from Jeff, Keno, Jameson or someone else involved with the >> internals of >> >> the compiler. Getting input from the broader community is the main >> reason I >> >> wanted to put a demo of OptionTypes.jl out in front of other folks. >> >> >> >> >> >> >> >> * I’m not clear how we could come to know that a datum is not missing >> >> without a resolution step that’s effectively equivalent to the get() >> >> function for Option{T}. I agree that the enforced use of get() means >> that >> >> you can’t hope to use generic functions like sum on collections of >> >> Option{T}. But I’m also not sure that’s such a bad thing: I think the >> >> easiest way to express to the compiler that you know that all of the >> entries >> >> of a DataArray are not NA is to convert the DataArray to a straight >> Array. >> >> But maybe you have other mechanisms for expressing this knowledge. >> Certainly >> >> my proposal to do conversions to Arrays isn’t the most elegant >> strategy. >> >> It’s just all that I’ve got so far. >> >> >> >> >> >> >> >> * I kind of like the idea of Option{T} standing outside of the main >> type >> >> system in a kind of mirror type system. I’m less happy about Union(NA, >> T) >> >> being a super type of T, even though there are some good reasons that >> you’d >> >> like to view T as a specialization of Union(NA, T). But I agree that I >> don’t >> >> have a good feel about where missing data belongs in the type >> hierarchy. >> >> This is another question for which I’d love to get input from others. >> >> >> >> >> >> >> >> In regard to Simon’s performance points: >> >> >> >> >> >> >> >> * Yes, memory usage alone argues strongly for working with DataArray{T} >> >> rather than Array{Option{T}}. >> >> >> >> >> >> >> >> * Exploting tricks that make operations like anyna() faster is another >> >> good argument for keeping DataArray{T} around. >> >> >> >> >> >> >> >> * I’m not sure how to deal with inlining concerns or the undefined >> >> reference checks. Do you have ideas for improving this within >> DataArrays or >> >> do we need supporting changes in the compiler? >> >> >> >> Actually it seems it would be possible to make Array{Union(NAtype, T)} >> >> more similar to and as efficient as DataArray{T}, by handling a few >> things >> >> in the compiler. This would create a generalization of DataArray to >> any kind >> >> of union type, which could be useful in other contexts. But more >> >> importantly, it would make missing values integrate seamlessly into >> Julia, >> >> getting rid of any hacks. >> >> >> >> More specifically, the following features would need to be supported: >> >> - a way of telling the compiler to store the data as two arrays of >> >> concrete types (here T and NAtype), instead of as an array of boxed >> values, >> >> so that: >> >> * efficient operations can be performed on the T values (by >> skipping >> >> the missing ones manually) >> >> * T values are stored as a dense array and can be converted to >> >> Array{T} without any copy or passed to BLAS when no missing values are >> >> present >> >> * NA values can be packed in a BitArray to save memory and make NA >> >> detection faster (see below) >> >> - a fonction to check whether a given element of the array is of type T >> >> rather than of NAtype (generalization of isna()) >> >> - a fonction to check whether all elements of the array are of type T >> >> rather than of NAtype (generalization of anyna(), more efficient than >> >> calling the previous function on all elements thanks to the packing of >> NAs >> >> in a BitArray) >> >> In this scheme, what is missing is how to allow the compiler to pack >> NAs >> >> in a BitArray. Somehow, NAtype would have to be defined as a 1-bit >> object. >> >> Maybe by making it an enum-like immutable with a 1-bit field inside it? >> >> >> >> How does it sound? >> > >> > >> > I've thought a bit about this, but it seems like it would be too much >> > complexity in the compiler. Storing arrays as something besides >> contiguous >> > elements and interaction between the codegen in C/C++ and the BitArray >> code >> > in Julia both seem likely to be painful, although Jeff, Keno, and >> Jameson >> > would know better than I. Additionally, this optimization (of storage of >> > arrays of unions of a singleton type and a bits type) seems pretty >> specific >> > to DataArrays, but the actual advantages in terms of performance and >> > expressibility would be small or non-existent. (This is in contrast to >> > optimizing storage/dispatch with union types, which could benefit a lot >> of >> > code and is something a lot of languages do.) Finally, there are cases >> where >> > it is useful to have direct access to the na BitArray chunks beyond >> anyna, >> > e.g. pairwise summation and reductions across the first dimension. >> > >> > Simon >> >
