Can someone explain these results to me.
Two functions:
f(x) = @fastmath cos(x)^3
f_float(x) = @fastmath cos(x)^3.0
Identical native code:
julia> code_native(f, (Float64,))
.text
Filename: none
Source line: 1
pushq %rbp
movq %rsp, %rbp
movabsq $cos, %rax
Source line: 1
callq *%rax
movabsq $140084090479408, %rax # imm = 0x7F67DE73A330
vmovsd (%rax), %xmm1
movabsq $pow, %rax
callq *%rax
popq %rbp
ret
julia> code_native(f_float, (Float64,))
.text
Filename: none
Source line: 1
pushq %rbp
movq %rsp, %rbp
movabsq $cos, %rax
Source line: 1
callq *%rax
movabsq $140084090501536, %rax # imm = 0x7F67DE73F9A0
vmovsd (%rax), %xmm1
movabsq $pow, %rax
callq *%rax
popq %rbp
ret
Still a large difference in performance:
function bench(N)
@time for i = 1:N
f(π/4)
end
@time for i = 1:N
f_float(π/4)
end
end
julia> bench(10^6)
0.062536 seconds
0.010077 seconds
Secondly, can someone explain why there should be a performance difference
at all? Is power by a float which is == an int defined differently? IEEE
shenanigans?
