Codon VS Kotlin benchmarks

Current benchmark data was generated on Thu Jul 13 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.)

helloworld

Input: QwQ

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
kotlin 1.kt 2.2ms 0.6ms 1.5MB 0ms 0ms kotlin/native 1.8.21
codon 1.py 4.0ms 0.6ms 5.1MB 0ms 0ms codon 0.16.2
kotlin 1.kt 65ms 4.9ms 40.9MB 50ms 10ms kotlin/jvm 17.0.2

nbody

Input: 5000000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
kotlin 1n.kt 532ms 5.2ms 1.5MB 517ms 0ms kotlin/native 1.8.21
kotlin 1.kt 576ms 4.4ms 42.8MB 577ms 17ms kotlin/jvm 17.0.2
codon 1.py 1947ms 41ms 7.2MB 1933ms 0ms codon 0.16.2

Input: 500000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
kotlin 1n.kt 55ms 0.1ms 1.5MB 50ms 0ms kotlin/native 1.8.21
kotlin 1.kt 148ms 2.5ms 43.4MB 150ms 10ms kotlin/jvm 17.0.2
codon 1.py 198ms 2.4ms 7.3MB 190ms 0ms codon 0.16.2

nsieve

Input: 12

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
codon 1.py 682ms 64ms 44.5MB 657ms 10ms codon 0.16.2
codon 2.py 911ms 35ms 104.9MB 883ms 13ms codon 0.16.2

Input: 10

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
codon 1.py 150ms 1.1ms 15.1MB 140ms 0ms codon 0.16.2
codon 2.py 202ms 0.9ms 25.6MB 183ms 7ms codon 0.16.2