[julia-users] Re: Lua Jit out performed Julia for my stock prediction engine use case
Pepsi challenge time?! Do you have a link to your data?
[julia-users] Re: Lua Jit out performed Julia for my stock prediction engine use case
My take on this is maturity: Lua is in version 5.3 (beta); Lua JIT version 2.0 vs Julia 0.3 (0.4 in dev) And as evidenced by the use of eg. @inbounds and @simd it still has a room for improvement (which is overall positive). This applies even more so to extra packages like DataFrames. Nevertheless I find Lua results quite impressive. It would be interesting to see how llvm-lua would perform, and if llvm makes any overhead on performance but I fear I am not the person who would be credible in even contemplating the answer, so it would be interesting to hear Julia's core developers take on this. On Monday, December 1, 2014 1:58:17 AM UTC+1, Joseph Ellsworth wrote: > > Just finished some basic tests comparing the lua jit and Julia for the > kinds of statistical functions we commonly compute. It essentially loads > 70K 1 minute bar records and computes a sma(14) and sma(600) for every row > in the file. This time I included source code so others can figure out > what I missed. It is admittedly a simplified case but I have found that > if this function runs fast the rest of our system tends to run fast so I > consider it a realistic starting benchmark. > > http://bayesanalytic.com/lua_jit_faster_than_julia_stock_prediction/ > > The results were not what I expected. I expected Julia to blow away > lua even with a jit due to the fact that I could allocate memory for result > arrays in typed arrays in Julia as blocks and couldn't figure out how to do > the same in lua. In addition the lua array index access seem more like a > hash rather than a pure numeric array index which should give Julia a > substantial advantage when looping across items in an array.What I > found is that Lua jit out performed Julia in all but 1 test even if you > don't consider Julia's horrible start-up performance. > > I am hoping that somebody finds a mistake that would make Julia out > perform as I really want to love it.I like the Julia community I also > really like the multi-dispatch function system. The Julia community seems > to be working at a incredible velocity but Julia's poor error messages, > slow startup time and letting lua beat them makes me skeptical for > investing in it for larger projects.On the other-hand Lua has been > around for a long time and is used as a scripting engine in many games and > consoles and is unlikely to go away anytime soon. > > If any of you produce a better Julia version that performs better then let > me know and I will add it to the original article.If any of you have a > chance to port the same code to Python to using pypy, Java, Scala, C then > let me know and I will add it to the original article. >
Re: [julia-users] Re: Lua Jit out performed Julia for my stock prediction engine use case
The sma_slice benchmark is ~6x faster on julia 0.4 if you use slice(avect, begndx:ndx) --Tim On Monday, December 01, 2014 04:46:38 AM Greg Trzeciak wrote: > My take on this is maturity: > > Lua is in version 5.3 (beta); Lua JIT version 2.0 vs Julia 0.3 (0.4 in dev) > > And as evidenced by the use of eg. @inbounds and @simd it still has a room > for improvement (which is overall positive). This applies even more so to > extra packages like DataFrames. > > Nevertheless I find Lua results quite impressive. It would be interesting > to see how llvm-lua would perform, and if llvm makes any overhead on > performance but I fear I am not the person who would be credible in even > contemplating the answer, so it would be interesting to hear Julia's core > developers take on this. > > On Monday, December 1, 2014 1:58:17 AM UTC+1, Joseph Ellsworth wrote: > > Just finished some basic tests comparing the lua jit and Julia for the > > kinds of statistical functions we commonly compute. It essentially loads > > 70K 1 minute bar records and computes a sma(14) and sma(600) for every > > row > > in the file. This time I included source code so others can figure out > > what I missed. It is admittedly a simplified case but I have found that > > if this function runs fast the rest of our system tends to run fast so I > > consider it a realistic starting benchmark. > > > > http://bayesanalytic.com/lua_jit_faster_than_julia_stock_prediction/ > > > > The results were not what I expected. I expected Julia to blow away > > lua even with a jit due to the fact that I could allocate memory for > > result > > arrays in typed arrays in Julia as blocks and couldn't figure out how to > > do > > the same in lua. In addition the lua array index access seem more like a > > hash rather than a pure numeric array index which should give Julia a > > substantial advantage when looping across items in an array.What I > > found is that Lua jit out performed Julia in all but 1 test even if you > > don't consider Julia's horrible start-up performance. > > > > I am hoping that somebody finds a mistake that would make Julia out > > perform as I really want to love it.I like the Julia community I also > > really like the multi-dispatch function system. The Julia community > > seems > > to be working at a incredible velocity but Julia's poor error messages, > > slow startup time and letting lua beat them makes me skeptical for > > investing in it for larger projects.On the other-hand Lua has been > > around for a long time and is used as a scripting engine in many games and > > consoles and is unlikely to go away anytime soon. > > > > If any of you produce a better Julia version that performs better then let > > me know and I will add it to the original article.If any of you have a > > chance to port the same code to Python to using pypy, Java, Scala, C > > then > > let me know and I will add it to the original article.
