On Monday, 18 July 2016 13:27:09 UTC+3, Michael Jones wrote:
>
> Anything much faster than this needs vector operations in the interpreter 
> so the “get to the OP function” overhead is once per time series rather 
> than once per element in the series.
>

I managed to make it a little faster https://play.golang.org/p/Tr2PRKI23w, 
but runs only on windows (kind of).

*What have I done...*

+ Egon

 

>  
>
> *From: *<golan...@googlegroups.com <javascript:>> on behalf of Egon <
> egon...@gmail.com <javascript:>>
> *Date: *Monday, July 18, 2016 at 1:32 AM
> *To: *golang-nuts <golan...@googlegroups.com <javascript:>>
> *Cc: *<ondrej...@gmail.com <javascript:>>
> *Subject: *[go-nuts] Re: An efficient runtime expression evaluation
>
>  
>
>
>
> On Monday, 18 July 2016 11:13:08 UTC+3, Egon wrote:
>
>
>
> On Monday, 18 July 2016 10:30:14 UTC+3, Egon wrote:
>
> On Monday, 18 July 2016 03:11:29 UTC+3, ondrej...@gmail.com wrote:
>
> Cheers, I tried replicating my endeavours (
> https://play.golang.org/p/Qxoo2ASac6), sorry if it's still too verbose. 
> It's essentially rewriting the inbuilt ast.Node into a simpler nested 
> struct and then walking it.
>
>  
>
> In testing the performance, I started adding algebraic expressions, which 
> make my walking more expensive, but don't change the 'native' expression 
> evaluation (I guess due to constant folding).
>
>  
>
> As to your suggestion three - I do the variable lookup in the parsing 
> stage, but I still need to retain the pointer, not the value itself, 
> because I'm accessing an element of that given variable (time series), and 
> this element (time period) changes at runtime.
>
>  
>
> https://play.golang.org/p/dd4hTpMKrp
>
>  
>
> Of course you can additionally add constant folding and similar... 
> Additionally instead of working on a single float at a time, make each 
> variable an array of 8 floats, that are computed in parallel.
>
>  
>
>  
>
> Just realized that it's trivial to write basic constant folding: 
> https://play.golang.org/p/iqWX5_Mweb
>
>  
>
> Although it probably will be easier to maintain and extend as a separate 
> pass: https://play.golang.org/p/xcz5mXoaOG
>
>  
>
>  
>
> This brings the result to:
>
>  
>
> interpreter: 17.001ms
>
> native: 7.0004ms
>
>  
>
> Which is approximately the best I would expect from an interpreter without 
> JIT (and not computing multiple time-points at a time).
>
>  
>
> + Egon
>
>  
>
> One performance gain I can think of is to implement some pruning through 
> the abovementioned constant folding and other optimisations, but I'd rather 
> leave that as the last resort. Another thing that comes to mind is that I 
> could return nested closures in some way - meaning that '1+3*x' would be, 
> in go-like pseudocode, add(func() { return one }, func mul(func() { return 
> three}, func() {return model[x]} )), where the one/tree are values passed 
> to the closure when parsing the equation; but that's just now off the top 
> of my head.
>
>  
>
> I attached a pprof result in the header.
>
>  
>
> Thanks again.
>
>
> On Friday, 8 July 2016 15:46:32 UTC+1, Egon wrote:
>
> On Friday, 8 July 2016 16:25:40 UTC+3, Ondrej wrote:
>
> Hi all,
>
> I have a model with variables, let's call them a, b, c, ..., z. These are 
> numerical values (time series loaded from a database) and I let the user 
> specify their relationships in a JSON, say 'z = 12; x = a + 2/3 + 3*c; y = 
> log(12*f) + exp(g)' etc. The syntax is trivial - it's basically just 
> algebraic relationships + a few functions (log, log2, log10, exp, 
> trigonometrics, ...; all 1:1 mappings to their math package equivalents).
>
>  
>
> *Tip: include a working piece of code that you want to make faster, it 
> makes it easier for people to see the problems and common issues.*
>
>  
>
>  
>
> Now, I get these relationships in a JSON and I parse them using go/parser. 
> Then I walk the tree once and process it a bit - replacing keywords by 
> pointers to my variable stores, replacing all the log/exp/sin with function 
> pointers, leaving literals be literals etc. Each node is then a struct with 
> a type and the actual contents (sadly a generic interface, because the 
> value can be almost anything). The prep stage is now over.
>
>  
>
> When actually running the model, I loop through years and within each year 
> I solve each variable - I walk the tree and evaluate it where needed. The 
> only non-trivial action is when I get to a model variable, I need to do a 
> bit of lookup (it's a time series, so I need to look up the correct time 
> period and other bits). Otherwise it's just literals, operators and 
> function calls, all of which is fairly straightforward.
>
>  
>
> This is all well and good. One of the issues is that it's rather slow. I 
> thought it would be the recursive nature (and interface assertions), but 
> converting all this into a shunting yard system didn't improve the 
> performance dramatically. I've profiled the thing and removed a few 
> hotspots, my question is not about profiling. I'm after a bit more general 
> advice on how to handle these runtime evaluations and if there are better 
> ways of doing so. Essentially some sort of a JIT (but Go does not have 
> runtime assembly, right?), or maybe convert each expression into a closure 
> or maybe a whole different algorithm or...?
>
>  
>
> Reduce the amount of code and indirection that you need to do, few basic 
> ideas:
>
> 1. implement a VM https://play.golang.org/p/dlmZ2lGPY7
>
> 2. operate on vectors of variables instead of single values 
> https://play.golang.org/p/25MIjIXs0D
>
> 3. try to do the lookup of all necessary variables before starting to 
> compute with them; if possible
>
>  
>
> Obviously pprof is your friend. (
> https://blog.golang.org/profiling-go-programs)
>
>  
>
> + Egon
>
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