No, because the point of the benchmarks is to compare the same algorithm across languages. Currently Julia and C use the same algorithm.
> On Dec 29, 2014, at 10:26 PM, [email protected] wrote: > > If this is the case I think there needs to be an update of the benchmarks. > > The few second percentages in performance only makes a difference when > processing massive datasets. > >> On Monday, December 29, 2014 6:05:21 PM UTC-8, Stefan Karpinski wrote: >> I just measured Julia's built-in quicksort against the C quicksort >> microbenchmark and Julia's built-in quicksort is 25% faster than C at its >> best optimization setting (which turns out to be -O2). Of course, you can >> argue that this is unfair because more time and effort has been put into >> Julia's quicksort than the simple C quicksort for that benchmark. This kind >> of back and forth can go on ad nauseum and isn't very productive. The >> message of those benchmarks is that you can write a fast sort in Julia code; >> obsessing about ±25% is missing the point. >> >>> On Mon, Dec 29, 2014 at 8:50 PM, Steven G. Johnson <[email protected]> >>> wrote: >>> In general, the philosophy of Julia is to be willing to pay a small price >>> (up to a factor of 2 compared to C, but usually less) in order to get the >>> benefit of a high-level, dynamic language with lots of other features that >>> C lacks (e.g. better error handling). >>> >>> The 24% slowdown in a simple quicksort implementation benchmark is well >>> within Julia's design tolerances. And, as I said, the actual sort routine >>> in the Julia standard library is actually faster than C's actual qsort >>> routine—unlike synthetic benchmarks, practical sorting routines have to >>> handle any datatype generically, and here Julia's type-specialization and >>> JIT compilation shine. >>> >>> In terms of why Go is 1.11 and Julia is 1.24 times C, when it comes to >>> these tiny differences you really need to at micro-level optimizations like >>> how bounds-checking or inlining is done, but frankly getting another 10% >>> here is a pretty low priority. It's much more important to improve >>> performance in other areas where Julia isn't yet so close to C for >>> straightforward code. >>
