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COLDTM: High Performance with Scilab Boosting your workflow – Boosting your Performances
Béatrice Creusillet & Thomas Izard ScilabTec 2015, Paris
2 - ScilabTec 2015
Development workflow
3 - ScilabTec 2015
Development workflow
4 - ScilabTec 2015
Development workflow
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From code to binaries or libraries
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▶ CFD applicaAon based on LaDce Boltzmann method1 ▶ IniAalizaAon step: cfd_init.sce ▶ Time loop:
– computaAon kernel: cfd_iteraAon.sce – visualizaAon – 10000 cycles (400000 originally)
1 From wiki.palabos.org/numerics:codes Copyright © 2006-‐2008 by Jonas LaW
A prac7cal case
7 - ScilabTec 2015
Performances
Scilab
Scilab +
COLD (kernel)
Scilab +
COLD (main script)
COLD
(executable)
average kernel duraAon
390 ms 24 ms 12 ms 12 ms
total Ame for 10000 cycles
1 h 3 min 39 s 1 min 56 s 1 min 52 s
speed-‐up x 16 x 31 x 32
Experimental condiAons: • Intel Core i7-‐3770 @ 3.40GHz, 16Go, Ubuntu 14.04 • Scilab 5.5.2, COLD 2.1, gcc 4.8.2
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Some more performances…
▶ Series of benchmarks from an industrial partner (Richelieu Project) ▶ Raw code, no calls to Scilab library funcAons or vector operaAons
Scilab 5.4.1 COLDTM 1.6.3 Speed-‐up
Mat_mul (100) Mat_vec_mul (1000) Mat_mul2 (100)
2.38 s 2.13 s 2.08 s
0.0011 s 0.0016 s 0.0016 s
x2000 x1300 x1300
Mymesh Skyline Matrice
0.64 s 14.55 s 11.96 s
0.0014 s 0.035 s 0.054 s
x450 x400 x200
Mymesh triangular mesh generaAon Skyline morse matrix indexing building Matrice morse matrix building
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COLD: a Scilab-‐to-‐C++ compiler
Inputs ▶ Scripts and/or funcAons ▶ Large subset of language basics
– scalar types (int, real, complex), N-‐D arrays, sparse matrices, structures – all control flow structures – user funcAons…
▶ Large subset of Scilab funcAons (> 200)
Outputs ▶ C++11 high-‐performance code ▶ Standalone executables from scripts ▶ Scilab libraries ▶ Libraries with specific interfaces (for integraAon in user libraries) ▶ Human-‐readable or obfuscated code
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COLD: specific features
High-‐performance C++ code ▶ Strong type inference mechanism: no dynamic run-‐Ame overhead ▶ CompilaAon opAmizaAons ▶ MathemaAcal opAmizaAons ▶ ParallelizaAon ▶ Extends input data-‐size / parameter values coverage
User friendliness ▶ Windows / Linux ▶ Compliance analysis to detect unsupported features and opAmizaAon
obstacles ▶ Fast compilaAon (5000 lines of Scilab: < 0.5s to generate C++ code)
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COLDTM …
… generates high-‐performance code from Scilab codes … ▶ stand-‐alone applica7ons ▶ op7mized libraries, re-‐usable from Scilab environment
… offers … ▶ reducAon of Ame-‐to-‐demo or Ame-‐to-‐product ▶ code obfuscaAon, intellectual property protec7on
… evolves con?nuously and benefits from … ▶ industrial partnerships (real use-‐cases) ▶ collaboraAve research projects (FUI Richelieu, FUI Similan, ITEA2 Mach)
… is a scalable product … ▶ on-‐demand customiza7on for specific needs
Contact us on cold-‐[email protected]
