vDSP_conv occasionally returns NANs - swift

Question

I'm using vDSP_conv to perform autocorrelation. Mostly it works just fine but every so often it's filling the output array with NaNs.
The code:
func corr_test() {
var pass = 0
var x = [Float]()
for i in 0..<2000 {
x.append(Float(i))
}
while true {
print("pass \(pass)")
let corr = autocorr(x)
if corr[1].isNaN {
print("!!!")
}
pass += 1
}
}
func autocorr(a: [Float]) -> [Float] {
let resultLen = a.count * 2 + 1
let padding = [Float].init(count: a.count, repeatedValue: 0.0)
let a_pad = padding + a + padding
var result = [Float].init(count: resultLen, repeatedValue: 0.0)
vDSP_conv(a_pad, 1, a_pad, 1, &result, 1, UInt(resultLen), UInt(a_pad.count))
return result
}
The output:
pass ...
pass 169
pass 170
pass 171
(lldb) p corr
([Float]) $R0 = 4001 values {
[0] = 2.66466637E+9
[1] = NaN
[2] = NaN
[3] = NaN
[4] = NaN
...
I'm not sure what's going on here. I think I'm handling the 0 padding correctly since if I weren't I don't think I'd be getting correct results 99% of the time.
Ideas? Gracias.

Answer 1

Figured it out. The key was this comment from https://developer.apple.com/library/mac/samplecode/vDSPExamples/Listings/DemonstrateConvolution_c.html :
// “The signal length is padded a bit. This length is not actually passed to the vDSP_conv routine; it is the number of elements
// that the signal array must contain. The SignalLength defined below is used to allocate space, and it is the filter length
// rounded up to a multiple of four elements and added to the result length. The extra elements give the vDSP_conv routine
// leeway to perform vector-load instructions, which load multiple elements even if they are not all used. If the caller did not
// guarantee that memory beyond the values used in the signal array were accessible, a memory access violation might result.”
“Padded a bit.” Thanks for being so specific. Anyway here's the final working product:
func autocorr(a: [Float]) -> [Float] {
let filterLen = a.count
let resultLen = filterLen * 2 - 1
let signalLen = ((filterLen + 3) & 0xFFFFFFFC) + resultLen
let padding1 = [Float].init(count: a.count - 1, repeatedValue: 0.0)
let padding2 = [Float].init(count: (signalLen - padding1.count - a.count), repeatedValue: 0.0)
let signal = padding1 + a + padding2
var result = [Float].init(count: resultLen, repeatedValue: 0.0)
vDSP_conv(signal, 1, a, 1, &result, 1, UInt(resultLen), UInt(filterLen))
// Remove the first n-1 values which are just mirrored from the end so that [0] always has the autocorrelation.
result.removeFirst(filterLen - 1)
return result
}
Note that the results here aren't normalized.