Acton VS Codon benchmarks

Current benchmark data was generated on Sun Jan 29 2023, full log can be found HERE

CONTRIBUTIONS are WELCOME!

[x86_64][2 cores] Intel(R) Xeon(R) Platinum 8370C CPU @ 2.80GHz (Model 106)

* -m in a file name stands for multi-threading or multi-processing

* -i in a file name stands for direct intrinsics usage. (Usage of simd intrinsics via libraries is not counted)

* -ffi in a file name stands for non-stdlib FFI usage

* (You may find time < time(user) + time(sys) for some non-parallelized programs, the overhead is from GC or JIT compiler, which are allowed to take advantage of multi-cores as that's more close to real-world scenarios.)

edigits

Input: 250001

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
acton 1.act 531ms 21ms 7.2MB 487ms 17ms actonc 0.14.2

Input: 100000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
acton 1.act 215ms 37ms 4.9MB 150ms 20ms actonc 0.14.2

helloworld

Input: QwQ

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
codon 1.py 4.1ms 0.8ms 5.3MB 0ms 0ms codon 0.15.4
acton 1.act 4.5ms 2.3ms 3.6MB 0ms 0ms actonc 0.14.2

pidigits

Input: 8000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
acton 1.act 4256ms 56ms 7.8MB 3890ms 727ms actonc 0.14.2

Input: 4000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
acton 1.act 1379ms 302ms 6.7MB 1203ms 253ms actonc 0.14.2