In trying to get to the bottom of slow performance on some resource-limited systems, I started up SystemBenchmark.jl for running a quick series of basic representative tests on a system to quantify performance across a few different areas. The whole test suite takes ~1.5 mins to run.
The package includes baked-in results from a standard 2019 9th gen i7 laptop with a nvidia GPU running 1.4.1 on Linux, for easy comparison.
Here’s a 2018 macbook pro (no nvidia gpu) compared to the reference, highlighting some surprisingly slow performance, particularly the SSD IO.
pkg>add https://github.com/ianshmean/SystemBenchmark.jl
julia> using SystemBenchmark
julia> res = comparetoref();
[ Info: CuArrays.functional() == false. No usable GPU detected
[ Info: Printing of results may be truncated. To view the full results use `show(res, allrows=true)`
julia> show(res, allrows=true, allcols=true)
25×5 DataFrames.DataFrame
│ Row │ cat │ testname │ ref_res │ test_res │ factor │
│ │ String │ String │ Any │ Any │ Any │
├─────┼─────────────┼───────────────────┼──────────────────────────────────────────┼──────────────────────────────────────────┼───────────┤
│ 1 │ info │ SysBenchVer │ 0.2.0 │ 0.2.0 │ Equal │
│ 2 │ info │ JuliaVer │ 1.4.1 │ 1.4.1 │ Equal │
│ 3 │ info │ OS │ Linux (x86_64-pc-linux-gnu) │ macOS (x86_64-apple-darwin18.7.0) │ Not Equal │
│ 4 │ info │ CPU │ Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz │ Intel(R) Core(TM) i7-8850H CPU @ 2.60GHz │ Not Equal │
│ 5 │ info │ WORD_SIZE │ 64 │ 64 │ Equal │
│ 6 │ info │ LIBM │ libopenlibm │ libopenlibm │ Equal │
│ 7 │ info │ LLVM │ libLLVM-8.0.1 (ORCJIT, skylake) │ libLLVM-8.0.1 (ORCJIT, skylake) │ Equal │
│ 8 │ info │ GPU │ GeForce GTX 1650 with Max-Q Design │ missing │ Not Equal │
│ 9 │ cpu │ FloatMul │ 1.159e-6 │ 1.766e-6 │ 1.52373 │
│ 10 │ cpu │ FusedMulAdd │ 1.7e-8 │ 3.8e-8 │ 2.23529 │
│ 11 │ cpu │ FloatSin │ 4.0540000000000005e-6 │ 5.722e-6 │ 1.41145 │
│ 12 │ cpu │ VecMulBroad │ 2.9813065326633165e-5 │ 4.89347e-5 │ 1.64138 │
│ 13 │ cpu │ CPUMatMul │ 0.018634 │ 0.037384 │ 2.00623 │
│ 14 │ cpu │ MatMulBroad │ 0.0043675 │ 0.0224699 │ 5.14481 │
│ 15 │ cpu │ 3DMulBroad │ 0.0010295999999999999 │ 0.0018749 │ 1.821 │
│ 16 │ cpu │ peakflops │ 1.7255522888933444e11 │ 2.08563e11 │ 1.20867 │
│ 17 │ cpu │ FFMPEGH264Write │ 107.505687 │ 153.187 │ 1.42492 │
│ 18 │ mem │ DeepCopy │ 0.00018644988864142538 │ 0.000212379 │ 1.13907 │
│ 19 │ diskio │ DiskWrite1KB │ 0.0318615 │ 0.145938 │ 4.5804 │
│ 20 │ diskio │ DiskWrite1MB │ 0.928177 │ 0.737279 │ 0.794331 │
│ 21 │ diskio │ DiskRead1KB │ 0.006769 │ 0.068964 │ 10.1882 │
│ 22 │ diskio │ DiskRead1MB │ 0.14344 │ 0.591229 │ 4.12179 │
│ 23 │ loading │ JuliaLoad │ 91.214667 │ 216.426 │ 2.37271 │
│ 24 │ compilation │ compilecache │ 207.988182 │ 348.355 │ 1.67488 │
│ 25 │ compilation │ create_expr_cache │ 0.84871 │ 13.9177 │ 16.3987 │
RFC:
Before this is released and versioned, I’m sure the tests could be improved & added to. I’d love to cover all the important factors that affects how fast a system is, and in particular how fast Julia is on that system. Feedback, PR’s and contributors very welcome!
25 Likes
It worked for me without issue. Very neat.
1 Like
Great! Please feel free to post results. It would be good to get samples to start to identify platform issues
Didn’t know if you wanted this to turn into a comparison thread haha
julia> comparison_df = compareToRef()
[ Info: CuArrays.functional() == false. No usable GPU detected
Compilation tests100%|███████████████████████████████████████████████████████| Time: 0:01:06
Reference system ----------------------
Julia Version 1.4.1
Commit 381693d3df* (2020-04-14 17:20 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, skylake)
GPU: GeForce GTX 1650 with Max-Q Design
Test system ---------------------------
Julia Version 1.4.1
Commit 381693d3df* (2020-04-14 17:20 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Core(TM) i5-8400 CPU @ 2.80GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, skylake)
12×5 DataFrames.DataFrame
│ Row │ cat │ testname │ ref_ms │ test_ms │ factor │
│ │ String │ String │ Float64 │ Float64 │ Float64 │
├─────┼─────────────┼─────────────────┼─────────────┼─────────────┼──────────┤
│ 1 │ cpu │ FloatMul │ 1.134e-6 │ 1.308e-6 │ 1.15344 │
│ 2 │ cpu │ FloatSin │ 4.051e-6 │ 4.295e-6 │ 1.06023 │
│ 3 │ cpu │ VecMulBroad │ 2.99025e-5 │ 3.24276e-5 │ 1.08444 │
│ 4 │ cpu │ CPUMatMul │ 0.018874 │ 0.020791 │ 1.10157 │
│ 5 │ cpu │ MatMulBroad │ 0.00413388 │ 0.00278917 │ 0.67471 │
│ 6 │ cpu │ 3DMulBroad │ 0.0010365 │ 0.0011558 │ 1.1151 │
│ 7 │ cpu │ FFMPEGH264Write │ 105.757 │ 113.865 │ 1.07667 │
│ 8 │ mem │ DeepCopy │ 0.000177074 │ 0.000155921 │ 0.880542 │
│ 9 │ diskio │ TempdirWrite │ 0.024308 │ 0.028252 │ 1.16225 │
│ 10 │ diskio │ TempdirRead │ 0.0049865 │ 0.00573367 │ 1.14984 │
│ 11 │ loading │ JuliaLoad │ 91.921 │ 103.476 │ 1.1257 │
│ 12 │ compilation │ compilecache │ 118.46 │ 157.12 │ 1.32635 │
1 Like
I’m gonna try this out on my wife’s old 2005 MacBook that I use as a garage shop computer. Wish me luck.
4 Likes
VideoIO dependency of SystemBenchmark.jl could not be built.
(base) sari@laptop:/tmp$ julia
Activating environment at `~/.julia/environments/dev-env/Project.toml`
_
_ _ _(_)_ | Documentation: https://docs.julialang.org
(_) | (_) (_) |
_ _ _| |_ __ _ | Type "?" for help, "]?" for Pkg help.
| | | | | | |/ _` | |
| | |_| | | | (_| | | Version 1.4.1 (2020-04-14)
_/ |\__'_|_|_|\__'_| | Official https://julialang.org/ release
|__/ |
(@dev-env) pkg> add https://github.com/ianshmean/SystemBenchmark.jl
Updating git-repo `https://github.com/ianshmean/SystemBenchmark.jl`
Updating registry at `~/.julia/registries/General`
Updating git-repo `https://github.com/JuliaRegistries/General.git`
Resolving package versions...
Updating `~/.julia/environments/dev-env/Project.toml`
[30cdaa97] + SystemBenchmark v0.1.0 #master (https://github.com/ianshmean/SystemBenchmark.jl)
Updating `~/.julia/environments/dev-env/Manifest.toml`
[fa961155] + CEnum v0.2.0
[3895d2a7] + CUDAapi v4.0.0
[c5f51814] + CUDAdrv v6.3.0
[be33ccc6] + CUDAnative v3.0.4
[f68482b8] + Cthulhu v1.0.2
[3a865a2d] + CuArrays v2.1.0
[e2ba6199] + ExprTools v0.1.1
[b22a6f82] ↑ FFMPEG_jll v4.1.0+2 ⇒ v4.1.0+3
[559328eb] ↑ FriBidi_jll v1.0.5+2 ⇒ v1.0.5+3
[0c68f7d7] + GPUArrays v3.2.0
[c1c5ebd0] ↑ LAME_jll v3.100.0+0 ⇒ v3.100.0+1
[929cbde3] + LLVM v1.4.1
[872c559c] + NNlib v0.6.6
[30cdaa97] + SystemBenchmark v0.1.0 #master (https://github.com/ianshmean/SystemBenchmark.jl)
[a759f4b9] + TimerOutputs v0.5.5
[d6d074c3] + VideoIO v0.6.7
[0ac62f75] ↑ libass_jll v0.14.0+1 ⇒ v0.14.0+2
[f638f0a6] ↑ libfdk_aac_jll v0.1.6+1 ⇒ v0.1.6+2
[f27f6e37] ↑ libvorbis_jll v1.3.6+3 ⇒ v1.3.6+4
[1270edf5] ↑ x264_jll v2019.5.25+1 ⇒ v2019.5.25+2
[dfaa095f] ↑ x265_jll v3.0.0+0 ⇒ v3.0.0+1
julia> using SystemBenchmark
[ Info: Precompiling SystemBenchmark [30cdaa97-48ad-4abc-9688-3a7175b8083d]
Deps path: /home/sari/.julia/packages/VideoIO/AZ2p0/src/../deps/deps.jl
ERROR: LoadError: LoadError: VideoIO not installed properly, run `] build VideoIO`, restart Julia and try again
Stacktrace:
[1] error(::String) at ./error.jl:33
[2] top-level scope at /home/sari/.julia/packages/VideoIO/AZ2p0/src/init.jl:8
[3] include(::Module, ::String) at ./Base.jl:377
[4] include(::String) at /home/sari/.julia/packages/VideoIO/AZ2p0/src/VideoIO.jl:1
[5] top-level scope at /home/sari/.julia/packages/VideoIO/AZ2p0/src/VideoIO.jl:17
[6] include(::Module, ::String) at ./Base.jl:377
[7] top-level scope at none:2
[8] eval at ./boot.jl:331 [inlined]
[9] eval(::Expr) at ./client.jl:449
[10] top-level scope at ./none:3
in expression starting at /home/sari/.julia/packages/VideoIO/AZ2p0/src/init.jl:6
in expression starting at /home/sari/.julia/packages/VideoIO/AZ2p0/src/VideoIO.jl:17
ERROR: LoadError: Failed to precompile VideoIO [d6d074c3-1acf-5d4c-9a43-ef38773959a2] to /home/sari/.julia/compiled/v1.4/VideoIO/tZxJ7_ZwCM6.ji.
Stacktrace:
[1] error(::String) at ./error.jl:33
[2] compilecache(::Base.PkgId, ::String) at ./loading.jl:1272
[3] _require(::Base.PkgId) at ./loading.jl:1029
[4] require(::Base.PkgId) at ./loading.jl:927
[5] require(::Module, ::Symbol) at ./loading.jl:922
[6] include(::Module, ::String) at ./Base.jl:377
[7] top-level scope at none:2
[8] eval at ./boot.jl:331 [inlined]
[9] eval(::Expr) at ./client.jl:449
[10] top-level scope at ./none:3
in expression starting at /home/sari/.julia/packages/SystemBenchmark/7SQzh/src/SystemBenchmark.jl:9
ERROR: Failed to precompile SystemBenchmark [30cdaa97-48ad-4abc-9688-3a7175b8083d] to /home/sari/.julia/compiled/v1.4/SystemBenchmark/GSlI1_ZwCM6.ji.
Stacktrace:
[1] error(::String) at ./error.jl:33
[2] compilecache(::Base.PkgId, ::String) at ./loading.jl:1272
[3] _require(::Base.PkgId) at ./loading.jl:1029
[4] require(::Base.PkgId) at ./loading.jl:927
[5] require(::Module, ::Symbol) at ./loading.jl:922
[6] eval(::Module, ::Any) at ./boot.jl:331
[7] eval_user_input(::Any, ::REPL.REPLBackend) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/REPL/src/REPL.jl:86
[8] run_backend(::REPL.REPLBackend) at /home/sari/.julia/packages/Revise/Pcs5V/src/Revise.jl:1073
[9] top-level scope at none:0
(@dev-env) pkg> build VideoIO
Building VideoIO → `~/.julia/packages/VideoIO/AZ2p0/deps/build.log`
┌ Error: Error building `VideoIO`:
│ ERROR: LoadError: LoadError: LibraryProduct(nothing, ["libbz2"], :libbzip2, "Prefix(/home/sari/.julia/packages/VideoIO/AZ2p0/deps/usr)") is not satisfied, cannot generate deps.jl!
│ Stacktrace:
│ [1] error(::String) at ./error.jl:33
│ [2] write_deps_file(::String, ::Array{LibraryProduct,1}; verbose::Bool, isolate::Bool) at /home/sari/.julia/packages/BinaryProvider/GeAtj/src/Products.jl:419
│ [3] top-level scope at /home/sari/.julia/packages/VideoIO/AZ2p0/deps/build_Bzip2.v1.0.6.jl:48
│ [4] include(::Module, ::String) at ./Base.jl:377
│ [5] include(::String) at /home/sari/.julia/packages/VideoIO/AZ2p0/deps/build.jl:52
│ [6] top-level scope at /home/sari/.julia/packages/VideoIO/AZ2p0/deps/build.jl:53
│ [7] include(::String) at ./client.jl:439
│ [8] top-level scope at none:5
│ in expression starting at /home/sari/.julia/packages/VideoIO/AZ2p0/deps/build_Bzip2.v1.0.6.jl:48
│ in expression starting at /home/sari/.julia/packages/VideoIO/AZ2p0/deps/build.jl:45
└ @ Pkg.Operations /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Pkg/src/Operations.jl:892
julia> versioninfo()
Julia Version 1.4.1
Commit 381693d3df* (2020-04-14 17:20 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, skylake)
Can you file an issue on the VideoIO repo? Include your versioninfo(). Thanks!
1 Like
Here’s a run on a fairly big machine:
Julia Version 1.4.1
Commit 381693d3df* (2020-04-14 17:20 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: AMD EPYC 7702P 64-Core Processor
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, znver1)
GPU: Tesla V100-PCIE-32GB
13×3 DataFrames.DataFrame
│ Row │ cat │ testname │ ms │
│ │ String │ String │ Float64 │
├─────┼─────────────┼─────────────────┼─────────────┤
│ 1 │ cpu │ FloatMul │ 1.52e-6 │
│ 2 │ cpu │ FloatSin │ 3.92e-6 │
│ 3 │ cpu │ VecMulBroad │ 3.38431e-5 │
│ 4 │ cpu │ CPUMatMul │ 0.04103 │
│ 5 │ cpu │ MatMulBroad │ 0.00326222 │
│ 6 │ cpu │ 3DMulBroad │ 0.001306 │
│ 7 │ cpu │ FFMPEGH264Write │ 135.54 │
│ 8 │ gpu │ GPUMatMul │ 0.010631 │
│ 9 │ mem │ DeepCopy │ 0.000208309 │
│ 10 │ diskio │ TempdirWrite │ 0.01806 │
│ 11 │ diskio │ TempdirRead │ 0.00413137 │
│ 12 │ loading │ JuliaLoad │ 192.236 │
│ 13 │ compilation │ compilecache │ 114.833 │
Nice package, @ianshmean!
2 Likes
Mmm, if we’re going to collect disk IO, it might be helpful to collect what disk it’s writing to, etc… that number should be very, very, hardware-dependent. 
4 Likes
True. Is there a function for that? or would it need some JLL-ed lib for cross-platform use?
A few more multi-threaded benchmarks would be fun, for high-cored systems.
Mmm, if we’re going to collect disk IO, it might be helpful to collect […]
Yes, and benchmarking disk-IO is tricky anyway, with caching, etc.
Here is my case.
Julia Version 1.4.1
Commit 381693d3df* (2020-04-14 17:20 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, skylake)
12×3 DataFrames.DataFrame
│ Row │ cat │ testname │ ms │
│ │ String │ String │ Float64 │
├─────┼─────────────┼─────────────────┼─────────────┤
│ 1 │ cpu │ FloatMul │ 1.343e-6 │
│ 2 │ cpu │ FloatSin │ 4.795e-6 │
│ 3 │ cpu │ VecMulBroad │ 3.44346e-5 │
│ 4 │ cpu │ CPUMatMul │ 0.0235135 │
│ 5 │ cpu │ MatMulBroad │ 0.00472 │
│ 6 │ cpu │ 3DMulBroad │ 0.0012303 │
│ 7 │ cpu │ FFMPEGH264Write │ 145.311 │
│ 8 │ mem │ DeepCopy │ 0.000199598 │
│ 9 │ diskio │ TempdirWrite │ 0.03236 │
│ 10 │ diskio │ TempdirRead │ 0.00647875 │
│ 11 │ loading │ JuliaLoad │ 111.799 │
│ 12 │ compilation │ compilecache │ 181.517 │
1 Like
my laptop
Julia Version 1.4.0
Commit b8e9a9ecc6 (2020-03-21 16:36 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: AMD Ryzen 3 2200U with Radeon Vega Mobile Gfx
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, znver1)
12×3 DataFrames.DataFrame
│ Row │ cat │ testname │ ms │
│ │ String │ String │ Float64 │
├─────┼─────────────┼─────────────────┼─────────────┤
│ 1 │ cpu │ FloatMul │ 1.502e-6 │
│ 2 │ cpu │ FloatSin │ 3.877e-6 │
│ 3 │ cpu │ VecMulBroad │ 4.31855e-5 │
│ 4 │ cpu │ CPUMatMul │ 0.052929 │
│ 5 │ cpu │ MatMulBroad │ 0.006578 │
│ 6 │ cpu │ 3DMulBroad │ 0.0018525 │
│ 7 │ cpu │ FFMPEGH264Write │ 229.939 │
│ 8 │ mem │ DeepCopy │ 0.000287719 │
│ 9 │ diskio │ TempdirWrite │ 0.0258485 │
│ 10 │ diskio │ TempdirRead │ 0.00469157 │
│ 11 │ loading │ JuliaLoad │ 151.288 │
│ 12 │ compilation │ compilecache │ 211.8 │
1 Like
Julia Version 1.4.1
Commit 381693d3df (2020-04-14 17:20 UTC)
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: AMD Ryzen Threadripper 2950X 16-Core Processor
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, znver1)
Environment:
JULIA_NUM_THREADS = 16
12×3 DataFrames.DataFrame
│ Row │ cat │ testname │ ms │
│ │ String │ String │ Float64 │
├─────┼─────────────┼─────────────────┼─────────────┤
│ 1 │ cpu │ FloatMul │ 1.173e-6 │
│ 2 │ cpu │ FloatSin │ 3.086e-6 │
│ 3 │ cpu │ VecMulBroad │ 3.03688e-5 │
│ 4 │ cpu │ CPUMatMul │ 0.0548195 │
│ 5 │ cpu │ MatMulBroad │ 0.00393119 │
│ 6 │ cpu │ 3DMulBroad │ 0.0013556 │
│ 7 │ cpu │ FFMPEGH264Write │ 160.176 │
│ 8 │ mem │ DeepCopy │ 0.000175691 │
│ 9 │ diskio │ TempdirWrite │ 0.014507 │
│ 10 │ diskio │ TempdirRead │ 0.003717 │
│ 11 │ loading │ JuliaLoad │ 138.079 │
│ 12 │ compilation │ compilecache │ 115.095 │
1 Like
A roughly 10 year old hp Elitebook 2560p:
Test system ---------------------------
Julia Version 1.4.1
Commit 381693d3df* (2020-04-14 17:20 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Core(TM) i7-2620M CPU @ 2.70GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, sandybridge)
12×5 DataFrames.DataFrame
│ Row │ cat │ testname │ ref_ms │ test_ms │ factor │
│ │ String │ String │ Float64 │ Float64 │ Float64 │
├─────┼─────────────┼─────────────────┼─────────────┼─────────────┼──────────┤
│ 1 │ cpu │ FloatMul │ 1.134e-6 │ 1.8e-6 │ 1.5873 │
│ 2 │ cpu │ FloatSin │ 4.051e-6 │ 5.933e-6 │ 1.46458 │
│ 3 │ cpu │ VecMulBroad │ 2.99025e-5 │ 9.58453e-5 │ 3.20526 │
│ 4 │ cpu │ CPUMatMul │ 0.018874 │ 0.065538 │ 3.4724 │
│ 5 │ cpu │ MatMulBroad │ 0.00413388 │ 0.00546733 │ 1.32257 │
│ 6 │ cpu │ 3DMulBroad │ 0.0010365 │ 0.0017305 │ 1.66956 │
│ 7 │ cpu │ FFMPEGH264Write │ 105.757 │ 225.935 │ 2.13636 │
│ 8 │ mem │ DeepCopy │ 0.000177074 │ 0.000612061 │ 3.45653 │
│ 9 │ diskio │ TempdirWrite │ 0.024308 │ 0.022627 │ 0.930846 │
│ 10 │ diskio │ TempdirRead │ 0.0049865 │ 0.0108317 │ 2.1722 │
│ 11 │ loading │ JuliaLoad │ 91.921 │ 158.841 │ 1.72802 │
│ 12 │ compilation │ compilecache │ 118.46 │ 249.303 │ 2.10453 │
1 Like
Julia Version 1.4.1
Commit 381693d3df* (2020-04-14 17:20 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: AMD Ryzen Threadripper 3970X 32-Core Processor
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, znver1)
GPU: GeForce RTX 2080 SUPER
13×3 DataFrames.DataFrame
│ Row │ cat │ testname │ ms │
│ │ String │ String │ Float64 │
├─────┼─────────────┼─────────────────┼─────────────┤
│ 1 │ cpu │ FloatMul │ 1.31e-6 │
│ 2 │ cpu │ FloatSin │ 5.27e-6 │
│ 3 │ cpu │ VecMulBroad │ 4.05241e-5 │
│ 4 │ cpu │ CPUMatMul │ 0.110252 │
│ 5 │ cpu │ MatMulBroad │ 0.00562 │
│ 6 │ cpu │ 3DMulBroad │ 0.001837 │
│ 7 │ cpu │ FFMPEGH264Write │ 130.607 │
│ 8 │ gpu │ GPUMatMul │ 0.00592143 │
│ 9 │ mem │ DeepCopy │ 0.000259325 │
│ 10 │ diskio │ TempdirWrite │ 0.0259005 │
│ 11 │ diskio │ TempdirRead │ 0.00472013 │
│ 12 │ loading │ JuliaLoad │ 186.623 │
│ 13 │ compilation │ compilecache │ 128.309 │
3 Likes
Thanks for the reports. I’m keen to get more MacOS and Linux ARM results, especially newer models 
Speaking of the devil, here’s mine (macOS), 2 years old this year.
Reference system ----------------------
Julia Version 1.4.1
Commit 381693d3df* (2020-04-14 17:20 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, skylake)
GPU: GeForce GTX 1650 with Max-Q Design
Test system ---------------------------
Julia Version 1.4.1
Commit 381693d3df* (2020-04-14 17:20 UTC)
Platform Info:
OS: macOS (x86_64-apple-darwin18.7.0)
CPU: Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, skylake)
12×5 DataFrames.DataFrame
│ Row │ cat │ testname │ ref_ms │ test_ms │ factor │
│ │ String │ String │ Float64 │ Float64 │ Float64 │
├─────┼─────────────┼─────────────────┼─────────────┼─────────────┼─────────┤
│ 1 │ cpu │ FloatMul │ 1.134e-6 │ 1.669e-6 │ 1.47178 │
│ 2 │ cpu │ FloatSin │ 4.051e-6 │ 4.667e-6 │ 1.15206 │
│ 3 │ cpu │ VecMulBroad │ 2.99025e-5 │ 4.62495e-5 │ 1.54668 │
│ 4 │ cpu │ CPUMatMul │ 0.018874 │ 0.03248 │ 1.72089 │
│ 5 │ cpu │ MatMulBroad │ 0.00413388 │ 0.0177087 │ 4.2838 │
│ 6 │ cpu │ 3DMulBroad │ 0.0010365 │ 0.001631 │ 1.57356 │
│ 7 │ cpu │ FFMPEGH264Write │ 105.757 │ 172.66 │ 1.63262 │
│ 8 │ mem │ DeepCopy │ 0.000177074 │ 0.000186826 │ 1.05508 │
│ 9 │ diskio │ TempdirWrite │ 0.024308 │ 0.191835 │ 7.89185 │
│ 10 │ diskio │ TempdirRead │ 0.0049865 │ 0.666844 │ 133.73 │
│ 11 │ loading │ JuliaLoad │ 91.921 │ 171.811 │ 1.86911 │
│ 12 │ compilation │ compilecache │ 118.46 │ 150.962 │ 1.27437 │
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Interesting… your diskio results are slow too. What model mac? I’m assuming your tempdir is on an SSD, like mine?