On Wed, Sep 21, 2016 at 9:49 PM, Erik Schnetter <[email protected]> wrote: > I confirm that I can't get Julia to synthesize a `vfmadd` instruction > either... Sorry for sending you on a wild goose chase.
-march=haswell does the trick for C (both clang and gcc) the necessary bit for the machine ir optimization (this is not a llvm ir optimization pass) to do this is llc options -mcpu=haswell and function attribute unsafe-fp-math=true. > > -erik > > On Wed, Sep 21, 2016 at 9:33 PM, Yichao Yu <[email protected]> wrote: >> >> On Wed, Sep 21, 2016 at 9:29 PM, Erik Schnetter <[email protected]> >> wrote: >> > On Wed, Sep 21, 2016 at 9:22 PM, Chris Rackauckas <[email protected]> >> > wrote: >> >> >> >> I'm not seeing `@fastmath` apply fma/muladd. I rebuilt the sysimg and >> >> now >> >> I get results where g and h apply muladd/fma in the native code, but a >> >> new >> >> function k which is `@fastmath` inside of f does not apply muladd/fma. >> >> >> >> >> >> https://gist.github.com/ChrisRackauckas/b239e33b4b52bcc28f3922c673a25910 >> >> >> >> Should I open an issue? >> > >> > >> > In your case, LLVM apparently thinks that `x + x + 3` is faster to >> > calculate >> > than `2x+3`. If you use a less round number than `2` multiplying `x`, >> > you >> > might see a different behaviour. >> >> I've personally never seen llvm create fma from mul and add. We might >> not have the llvm passes enabled if LLVM is capable of doing this at >> all. >> >> > >> > -erik >> > >> > >> >> Note that this is on v0.6 Windows. On Linux the sysimg isn't rebuilding >> >> for some reason, so I may need to just build from source. >> >> >> >> On Wednesday, September 21, 2016 at 6:22:06 AM UTC-7, Erik Schnetter >> >> wrote: >> >>> >> >>> On Wed, Sep 21, 2016 at 1:56 AM, Chris Rackauckas <[email protected]> >> >>> wrote: >> >>>> >> >>>> Hi, >> >>>> First of all, does LLVM essentially fma or muladd expressions like >> >>>> `a1*x1 + a2*x2 + a3*x3 + a4*x4`? Or is it required that one >> >>>> explicitly use >> >>>> `muladd` and `fma` on these types of instructions (is there a macro >> >>>> for >> >>>> making this easier)? >> >>> >> >>> >> >>> Yes, LLVM will use fma machine instructions -- but only if they lead >> >>> to >> >>> the same round-off error as using separate multiply and add >> >>> instructions. If >> >>> you do not care about the details of conforming to the IEEE standard, >> >>> then >> >>> you can use the `@fastmath` macro that enables several optimizations, >> >>> including this one. This is described in the manual >> >>> >> >>> <http://docs.julialang.org/en/release-0.5/manual/performance-tips/#performance-annotations>. >> >>> >> >>> >> >>>> Secondly, I am wondering if my setup is no applying these >> >>>> operations >> >>>> correctly. Here's my test code: >> >>>> >> >>>> f(x) = 2.0x + 3.0 >> >>>> g(x) = muladd(x,2.0, 3.0) >> >>>> h(x) = fma(x,2.0, 3.0) >> >>>> >> >>>> @code_llvm f(4.0) >> >>>> @code_llvm g(4.0) >> >>>> @code_llvm h(4.0) >> >>>> >> >>>> @code_native f(4.0) >> >>>> @code_native g(4.0) >> >>>> @code_native h(4.0) >> >>>> >> >>>> Computer 1 >> >>>> >> >>>> Julia Version 0.5.0-rc4+0 >> >>>> Commit 9c76c3e* (2016-09-09 01:43 UTC) >> >>>> Platform Info: >> >>>> System: Linux (x86_64-redhat-linux) >> >>>> CPU: Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz >> >>>> WORD_SIZE: 64 >> >>>> BLAS: libopenblas (DYNAMIC_ARCH NO_AFFINITY Haswell) >> >>>> LAPACK: libopenblasp.so.0 >> >>>> LIBM: libopenlibm >> >>>> LLVM: libLLVM-3.7.1 (ORCJIT, broadwell) >> >>> >> >>> >> >>> This looks good, the "broadwell" architecture that LLVM uses should >> >>> imply >> >>> the respective optimizations. Try with `@fastmath`. >> >>> >> >>> -erik >> >>> >> >>> >> >>> >> >>> >> >>>> >> >>>> (the COPR nightly on CentOS7) with >> >>>> >> >>>> [crackauc@crackauc2 ~]$ lscpu >> >>>> Architecture: x86_64 >> >>>> CPU op-mode(s): 32-bit, 64-bit >> >>>> Byte Order: Little Endian >> >>>> CPU(s): 16 >> >>>> On-line CPU(s) list: 0-15 >> >>>> Thread(s) per core: 1 >> >>>> Core(s) per socket: 8 >> >>>> Socket(s): 2 >> >>>> NUMA node(s): 2 >> >>>> Vendor ID: GenuineIntel >> >>>> CPU family: 6 >> >>>> Model: 79 >> >>>> Model name: Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz >> >>>> Stepping: 1 >> >>>> CPU MHz: 1200.000 >> >>>> BogoMIPS: 6392.58 >> >>>> Virtualization: VT-x >> >>>> L1d cache: 32K >> >>>> L1i cache: 32K >> >>>> L2 cache: 256K >> >>>> L3 cache: 25600K >> >>>> NUMA node0 CPU(s): 0-7 >> >>>> NUMA node1 CPU(s): 8-15 >> >>>> >> >>>> >> >>>> >> >>>> I get the output >> >>>> >> >>>> define double @julia_f_72025(double) #0 { >> >>>> top: >> >>>> %1 = fmul double %0, 2.000000e+00 >> >>>> %2 = fadd double %1, 3.000000e+00 >> >>>> ret double %2 >> >>>> } >> >>>> >> >>>> define double @julia_g_72027(double) #0 { >> >>>> top: >> >>>> %1 = call double @llvm.fmuladd.f64(double %0, double 2.000000e+00, >> >>>> double 3.000000e+00) >> >>>> ret double %1 >> >>>> } >> >>>> >> >>>> define double @julia_h_72029(double) #0 { >> >>>> top: >> >>>> %1 = call double @llvm.fma.f64(double %0, double 2.000000e+00, >> >>>> double >> >>>> 3.000000e+00) >> >>>> ret double %1 >> >>>> } >> >>>> .text >> >>>> Filename: fmatest.jl >> >>>> pushq %rbp >> >>>> movq %rsp, %rbp >> >>>> Source line: 1 >> >>>> addsd %xmm0, %xmm0 >> >>>> movabsq $139916162906520, %rax # imm = 0x7F40C5303998 >> >>>> addsd (%rax), %xmm0 >> >>>> popq %rbp >> >>>> retq >> >>>> nopl (%rax,%rax) >> >>>> .text >> >>>> Filename: fmatest.jl >> >>>> pushq %rbp >> >>>> movq %rsp, %rbp >> >>>> Source line: 2 >> >>>> addsd %xmm0, %xmm0 >> >>>> movabsq $139916162906648, %rax # imm = 0x7F40C5303A18 >> >>>> addsd (%rax), %xmm0 >> >>>> popq %rbp >> >>>> retq >> >>>> nopl (%rax,%rax) >> >>>> .text >> >>>> Filename: fmatest.jl >> >>>> pushq %rbp >> >>>> movq %rsp, %rbp >> >>>> movabsq $139916162906776, %rax # imm = 0x7F40C5303A98 >> >>>> Source line: 3 >> >>>> movsd (%rax), %xmm1 # xmm1 = mem[0],zero >> >>>> movabsq $139916162906784, %rax # imm = 0x7F40C5303AA0 >> >>>> movsd (%rax), %xmm2 # xmm2 = mem[0],zero >> >>>> movabsq $139925776008800, %rax # imm = 0x7F43022C8660 >> >>>> popq %rbp >> >>>> jmpq *%rax >> >>>> nopl (%rax) >> >>>> >> >>>> It looks like explicit muladd or not ends up at the same native code, >> >>>> but is that native code actually doing an fma? The fma native is >> >>>> different, >> >>>> but from a discussion on the Gitter it seems that might be a software >> >>>> FMA? >> >>>> This computer is setup with the BIOS setting as LAPACK optimized or >> >>>> something like that, so is that messing with something? >> >>>> >> >>>> Computer 2 >> >>>> >> >>>> Julia Version 0.6.0-dev.557 >> >>>> Commit c7a4897 (2016-09-08 17:50 UTC) >> >>>> Platform Info: >> >>>> System: NT (x86_64-w64-mingw32) >> >>>> CPU: Intel(R) Core(TM) i7-4770K CPU @ 3.50GHz >> >>>> WORD_SIZE: 64 >> >>>> BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell) >> >>>> LAPACK: libopenblas64_ >> >>>> LIBM: libopenlibm >> >>>> LLVM: libLLVM-3.7.1 (ORCJIT, haswell) >> >>>> >> >>>> >> >>>> on a 4770k i7, Windows 10, I get the output >> >>>> >> >>>> ; Function Attrs: uwtable >> >>>> define double @julia_f_66153(double) #0 { >> >>>> top: >> >>>> %1 = fmul double %0, 2.000000e+00 >> >>>> %2 = fadd double %1, 3.000000e+00 >> >>>> ret double %2 >> >>>> } >> >>>> >> >>>> ; Function Attrs: uwtable >> >>>> define double @julia_g_66157(double) #0 { >> >>>> top: >> >>>> %1 = call double @llvm.fmuladd.f64(double %0, double 2.000000e+00, >> >>>> double 3.000000e+00) >> >>>> ret double %1 >> >>>> } >> >>>> >> >>>> ; Function Attrs: uwtable >> >>>> define double @julia_h_66158(double) #0 { >> >>>> top: >> >>>> %1 = call double @llvm.fma.f64(double %0, double 2.000000e+00, >> >>>> double >> >>>> 3.000000e+00) >> >>>> ret double %1 >> >>>> } >> >>>> .text >> >>>> Filename: console >> >>>> pushq %rbp >> >>>> movq %rsp, %rbp >> >>>> Source line: 1 >> >>>> addsd %xmm0, %xmm0 >> >>>> movabsq $534749456, %rax # imm = 0x1FDFA110 >> >>>> addsd (%rax), %xmm0 >> >>>> popq %rbp >> >>>> retq >> >>>> nopl (%rax,%rax) >> >>>> .text >> >>>> Filename: console >> >>>> pushq %rbp >> >>>> movq %rsp, %rbp >> >>>> Source line: 2 >> >>>> addsd %xmm0, %xmm0 >> >>>> movabsq $534749584, %rax # imm = 0x1FDFA190 >> >>>> addsd (%rax), %xmm0 >> >>>> popq %rbp >> >>>> retq >> >>>> nopl (%rax,%rax) >> >>>> .text >> >>>> Filename: console >> >>>> pushq %rbp >> >>>> movq %rsp, %rbp >> >>>> movabsq $534749712, %rax # imm = 0x1FDFA210 >> >>>> Source line: 3 >> >>>> movsd dcabs164_(%rax), %xmm1 # xmm1 = mem[0],zero >> >>>> movabsq $534749720, %rax # imm = 0x1FDFA218 >> >>>> movsd (%rax), %xmm2 # xmm2 = mem[0],zero >> >>>> movabsq $fma, %rax >> >>>> popq %rbp >> >>>> jmpq *%rax >> >>>> nop >> >>>> >> >>>> This seems to be similar to the first result. >> >>>> >> >>> >> >>> >> >>> >> >>> -- >> >>> Erik Schnetter <[email protected]> >> >>> http://www.perimeterinstitute.ca/personal/eschnetter/ >> > >> > >> > >> > >> > -- >> > Erik Schnetter <[email protected]> >> > http://www.perimeterinstitute.ca/personal/eschnetter/ > > > > > -- > Erik Schnetter <[email protected]> > http://www.perimeterinstitute.ca/personal/eschnetter/
