# NaNs In The Output of SVD
**URL:** https://discourse.julialang.org/t/nans-in-the-output-of-svd/93712
**Category:** Numerics
**Tags:** linearalgebra, svd
**Created:** [January 28, 2023, 8:44pm UTC](https://discourse.julialang.org/t/nans-in-the-output-of-svd/93712 "2023-01-28T20:44:57Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@robin-armstrong](https://discourse.julialang.org/u/robin-armstrong)
#### Post date: [January 28, 2023, 8:44pm UTC](https://discourse.julialang.org/t/nans-in-the-output-of-svd/93712/1 "2023-01-28T20:44:57Z")
I am currently running numerical experiments which involve computing the SVD of a very large number of random matrices. Occasionally, Julia’s SVD function will return a Vt factor that contains a row of all NaNs. Here is some code which reproduces this behavior in Julia 1.8.5 and 1.8.1, using updated versions of LinearAlgebra and Random.
```julia
using LinearAlgebra
using Random
# constructing the matrix
rng = MersenneTwister(17, (0, 181935856, 181934854, 579))
D = Diagonal([ones(100); exp10.(range(0, -12, 50)); 1e-12*ones(100)])
Q = Matrix(qr(D*randn(rng, 250, 150)).Q)
A = Q'*D
svd(A).Vt # 139th row is all NaNs
```
This bug can be difficult to detect, since no error messages are thrown by the SVD to indicate an abnormal result. Running the SVD with `alg = LinearAlgebra.QRIteration()` fixes the issue, but I believe this algorithm is slower.
I hope this is useful information, and I am curious about the source of the error! Thank you for your time.
---
### Author:  [@Ralph\_Smith](https://discourse.julialang.org/u/Ralph_Smith)
#### Post date: [January 28, 2023, 10:22pm UTC](https://discourse.julialang.org/t/nans-in-the-output-of-svd/93712/2 "2023-01-28T22:22:47Z")
It may be a bug in the multithreading logic in OpenBLAS. I consistently get the NaN result with 6 or 8 threads, but no other number, so I suspect buffer mismanagement rather than a race condition.
I don’t see any NaNs when using MKL, which may also be faster.