(we here use @noinline to prevent the opti- mizer from trying to be too clever and defeat our benchmark): @noinline function inner(x, y) s = zero(eltype(x)) for i=eachindex(x) @inbounds s += x[i]*y[i] – in general, the speedup will be smaller. (In this particular example, the working set of the benchmark is small enough to fit into the L1 cache of the processor, so that memory access latency does not Base.sin – Method. sin(x) Compute sine of x, where x is in radians. See also sind, sinpi, sincos, cis, asin. Examples julia> round.(sin.(range(0, 2pi, length=9)'), digits=3) 1×9 Matrix{Float64}: 0

(we here use @noinline to prevent the opti- mizer from trying to be too clever and defeat our benchmark): @noinline function inner(x, y) s = zero(eltype(x)) for i=eachindex(x) @inbounds s += x[i]*y[i] – in general, the speedup will be smaller. (In this particular example, the working set of the benchmark is small enough to fit into the L1 cache of the processor, so that memory access latency does not Base.sin – Method. sin(x) Compute sine of x, where x is in radians. See also sind, sinpi, sincos, cis, asin. Examples julia> round.(sin.(range(0, 2pi, length=9)'), digits=3) 1×9 Matrix{Float64}: 0

markup (we here use @noinline to prevent the optimizer from trying to be too clever and defeat our benchmark): CHAPTER 34. PERFORMANCE TIPS 393 @noinline function inner(x, y) s = zero(eltype(x)) for i=eachindex(x) – in general, the speedup will be smaller. (In this particular example, the working set of the benchmark is small enough to fit into the L1 cache of the processor, so that memory access latency does not See also [sind], [sinpi], [sincos], [cis]. source Base.cos – Method. cos(x) Compute cosine of x, where x is in radians. See also [cosd], [cospi], [sincos], [cis]. source Base.Math.sincos – Method

(we here use @noinline to prevent the opti- mizer from trying to be too clever and defeat our benchmark): @noinline function inner(x, y) s = zero(eltype(x)) for i=eachindex(x) @inbounds s += x[i]*y[i] – in general, the speedup will be smaller. (In this particular example, the working set of the benchmark is small enough to fit into the L1 cache of the processor, so that memory access latency does not Compute sine of x, where x is in radians.CHAPTER 44. MATHEMATICS 850 See also sind, sinpi, sincos, cis, asin. Examples julia> round.(sin.(range(0, 2pi, length=9)'), digits=3) 1×9 Matrix{Float64}: 0

(we here use @noinline to prevent the opti- mizer from trying to be too clever and defeat our benchmark): @noinline function inner(x, y) s = zero(eltype(x)) for i=eachindex(x) @inbounds s += x[i]*y[i] – in general, the speedup will be smaller. (In this particular example, the working set of the benchmark is small enough to fit into the L1 cache of the processor, so that memory access latency does not Compute sine of x, where x is in radians.CHAPTER 44. MATHEMATICS 850 See also sind, sinpi, sincos, cis, asin. Examples julia> round.(sin.(range(0, 2pi, length=9)'), digits=3) 1×9 Matrix{Float64}: 0

(we here use @noinline to prevent the opti- mizer from trying to be too clever and defeat our benchmark): @noinline function inner(x, y) s = zero(eltype(x)) for i=eachindex(x) @inbounds s += x[i]*y[i] – in general, the speedup will be smaller. (In this particular example, the working set of the benchmark is small enough to fit into the L1 cache of the processor, so that memory access latency does not Base.sin – Method. sin(x) Compute sine of x, where x is in radians. See also sind, sinpi, sincos, cis, asin. Examples julia> round.(sin.(range(0, 2pi, length=9)'), digits=3) 1×9 Matrix{Float64}: 0

(we here use @noinline to prevent the opti- mizer from trying to be too clever and defeat our benchmark): @noinline function inner(x, y) s = zero(eltype(x)) for i=eachindex(x) @inbounds s += x[i]*y[i] – in general, the speedup will be smaller. (In this particular example, the working set of the benchmark is small enough to fit into the L1 cache of the processor, so that memory access latency does not Base.sin – Method. sin(x) Compute sine of x, where x is in radians. See also sind, sinpi, sincos, cis, asin. Examples julia> round.(sin.(range(0, 2pi, length=9)'), digits=3) 1×9 Matrix{Float64}: 0

(we here use @noinline to prevent the opti- mizer from trying to be too clever and defeat our benchmark): @noinline function inner(x, y) s = zero(eltype(x)) for i=eachindex(x) @inbounds s += x[i]*y[i] – in general, the speedup will be smaller. (In this particular example, the working set of the benchmark is small enough to fit into the L1 cache of the processor, so that memory access latency does not Base.sin – Method. sin(x) Compute sine of x, where x is in radians. See also sind, sinpi, sincos, cis, asin. Examples julia> round.(sin.(range(0, 2pi, length=9)'), digits=3) 1×9 Matrix{Float64}: 0

(we here use @noinline to prevent the opti- mizer from trying to be too clever and defeat our benchmark): @noinline function inner(x, y) s = zero(eltype(x)) for i=eachindex(x) @inbounds s += x[i]*y[i] – in general, the speedup will be smaller. (In this particular example, the working set of the benchmark is small enough to fit into the L1 cache of the processor, so that memory access latency does not Base.sin – Method. sin(x) Compute sine of x, where x is in radians. See also sind, sinpi, sincos, cis, asin. Examples julia> round.(sin.(range(0, 2pi, length=9)'), digits=3) 1×9 Matrix{Float64}: 0

(we here use @noinline to prevent the opti- mizer from trying to be too clever and defeat our benchmark): @noinline function inner(x, y) s = zero(eltype(x)) for i=eachindex(x) @inbounds s += x[i]*y[i] – in general, the speedup will be smaller. (In this particular example, the working set of the benchmark is small enough to fit into the L1 cache of the processor, so that memory access latency does not Base.sin – Method. sin(x) Compute sine of x, where x is in radians. See also sind, sinpi, sincos, cis, asin. Examples julia> round.(sin.(range(0, 2pi, length=9)'), digits=3) 1×9 Matrix{Float64}: 0