7 ms·

I'm always found Julia performance claims [1] to be misleading in comparison to LuaJit [2]. Because Julia claims to be much faster than LuaJIT, yet continually

I'm always found Julia performance claims [1] to be misleading in comparison to LuaJit [2]. Because Julia claims to be much faster than LuaJIT, yet continually - people find that LuaJIT (not Julia) is much faster in real world test [3]. Does anyone else have experience in Julia vs LuaJIT? [1] http://julialang.org/#high-performance-jit-compiler http://julialang.org/#high-performance-jit-compiler [2] http://luajit.org/performance_x86.html http://luajit.org/performance_x86.html [3] http://bayesanalytic.com/lua_jit_faster_than_julia_stock_prediction/ http://bayesanalytic.com/lua_jit_faster_than_julia_stock_pre...

acidflask 11y ago
Improvements to our LuaJIT benchmarking are currently being discussed in https://github.com/JuliaLang/julia/issues/14222 https://github.com/JuliaLang/julia/issues/14222. LuaJIT 2.1 is significantly faster than LuaJIT 2.0, but until now I haven't had a convenient way to get an installation of LuaJIT 2.1 on our test machine. LuaSci was easy to install and we would be amenable to switching over to LuaSci instead of vanilla gsl-shell. See https://github.com/JuliaLang/julia/issues/14222#issuecomment-161117689 https://github.com/JuliaLang/julia/issues/14222#issuecomment... for a timing comparison.
- tiffanyh 11y ago
  Thanks for the note. Appreciate the transparency
- baldfat 11y ago
  I never looked at SciLua till just now. I have always liked Lua and have made several scripts for my desktop and servers. Just never thought of Lua for Data Science. My main issue is I haven't hit a data set to big for R in my own use cases.
johnmyleswhite 11y ago
I think it would be really interesting to understand exactly why Julia underperforms LuaJIT on some benchmarks. I'm pretty skeptical that Julia loses to LuaJIT uniformly; I suspect it depends on the benchmark taking advantage of LuaJIT's superior discovery of run-time type information.
baldfat 11y ago
I find benchmarking to be of little value when the percentages are small. The differences are tiny when I see them don.
CyberDildonics 11y ago
Julia in contrast to most languages can run very fast or very slow for roughly the same program because of type information and garbage collection. I would be willing to bet there is a lot of fat to be trimmed if you can't get close to LuaJIT unless SIMD is involved. Have you tried profiling your Julia code to see where the problem is?

acidflask 11y ago

Improvements to our LuaJIT benchmarking are currently being discussed in https://github.com/JuliaLang/julia/issues/14222 https://github.com/JuliaLang/julia/issues/14222. LuaJIT 2.1 is significantly faster than LuaJIT 2.0, but until now I haven't had a convenient way to get an installation of LuaJIT 2.1 on our test machine. LuaSci was easy to install and we would be amenable to switching over to LuaSci instead of vanilla gsl-shell. See https://github.com/JuliaLang/julia/issues/14222#issuecomment-161117689 https://github.com/JuliaLang/julia/issues/14222#issuecomment... for a timing comparison.

tiffanyh 11y ago
Thanks for the note. Appreciate the transparency
baldfat 11y ago
I never looked at SciLua till just now. I have always liked Lua and have made several scripts for my desktop and servers. Just never thought of Lua for Data Science. My main issue is I haven't hit a data set to big for R in my own use cases.

johnmyleswhite 11y ago

I think it would be really interesting to understand exactly why Julia underperforms LuaJIT on some benchmarks. I'm pretty skeptical that Julia loses to LuaJIT uniformly; I suspect it depends on the benchmark taking advantage of LuaJIT's superior discovery of run-time type information.

baldfat 11y ago

I find benchmarking to be of little value when the percentages are small. The differences are tiny when I see them don.

CyberDildonics 11y ago

Julia in contrast to most languages can run very fast or very slow for roughly the same program because of type information and garbage collection. I would be willing to bet there is a lot of fat to be trimmed if you can't get close to LuaJIT unless SIMD is involved. Have you tried profiling your Julia code to see where the problem is?