Codon VS Chapel benchmarks

Current benchmark data was generated on Tue Dec 31 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
codon 1.py 4.0ms 0.7ms 7.1MB 0ms 0ms codon 0.17.0
chapel 1.chpl 17ms 1.9ms 32.8MB 10ms 0ms chpl 1.31.0

nbody

Input: 5000000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
chapel 2.chpl 310ms 1.1ms 32.8MB 300ms 0ms chpl 1.31.0
codon 1.py 1232ms 11ms 5.8MB 1220ms 0ms codon 0.17.0

Input: 500000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
chapel 2.chpl 49ms 1.1ms 32.9MB 43ms 0ms chpl 1.31.0
codon 1.py 131ms 4.2ms 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 348ms 9.8ms 46.5MB 333ms 0ms codon 0.17.0
codon 2.py 805ms 5.6ms 99.9MB 790ms 13ms codon 0.17.0

Input: 10

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
codon 1.py 71ms 1.3ms 15.3MB 57ms 0ms codon 0.17.0
codon 2.py 185ms 0.8ms 25.8MB 170ms 3ms codon 0.17.0