Codon VS Kotlin benchmarks

Current benchmark data was generated on Sun Dec 01 2024, full log can be found HERE

CONTRIBUTIONS are WELCOME!

[x86_64][4 cores] AMD EPYC 7763 64-Core Processor (Model 1)

* -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.)

helloworld

Input: QwQ

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
kotlin 1.kt 2.4ms 0.2ms 4.7MB 0ms 0ms kotlin/native 1.8.21
codon 1.py 4.2ms 0.5ms 6.9MB 0ms 0ms codon 0.17.0
kotlin 1.kt 58ms 4.7ms 47.4MB 56ms 16ms kotlin/jvm 21

nbody

Input: 5000000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
kotlin 1n.kt 407ms 3.6ms 4.7MB 400ms 0ms kotlin/native 1.8.21
kotlin 1.kt 446ms 1.4ms 49.5MB 480ms 23ms kotlin/jvm 21
codon 1.py 1306ms 9.3ms 7.7MB 1293ms 0ms codon 0.17.0

Input: 500000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
kotlin 1n.kt 46ms 0.7ms 4.7MB 40ms 0ms kotlin/native 1.8.21
kotlin 1.kt 123ms 1.1ms 49.4MB 163ms 20ms kotlin/jvm 21
codon 1.py 136ms 1.5ms 7.7MB 120ms 0ms codon 0.17.0

nsieve

Input: 12

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
codon 1.py 388ms 15ms 46.5MB 370ms 3ms codon 0.17.0
codon 2.py 904ms 9.6ms 99.9MB 880ms 20ms codon 0.17.0

Input: 10

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
codon 1.py 74ms 3.4ms 17.3MB 63ms 0ms codon 0.17.0
codon 2.py 199ms 0.4ms 25.7MB 190ms 0ms codon 0.17.0