SVD Algorithm Throws Errors for Large Matrices

I’ve been using the intel MKL implementation of SVD() through Math.NET numerics. I’ve had success running the algorithm. However, for very large matrices (in this case 64,000 x 500), I get the following error:

 Unhandled exception. System.OverflowException: Arithmetic operation resulted in an overflow.
 at MathNet.Numerics.LinearAlgebra.Storage.DenseColumnMajorMatrixStorage`1..ctor(Int32 rows, Int32 columns)
 at MathNet.Numerics.LinearAlgebra.Double.DenseMatrix..ctor(Int32 order)
 at MathNet.Numerics.LinearAlgebra.Double.Factorization.DenseSvd.Create(DenseMatrix matrix, Boolean computeVectors)
 at MathNet.Numerics.LinearAlgebra.Double.DenseMatrix.Svd(Boolean computeVectors) 

My questions are: Is this an inherent limitation in the MKL when using with large matrices? Is this a feature of the C# code and I’ve hit the upper limit of the size of the matrix? Is there a hot fix you could suggest that could be implemented to allow the library to be run on larger matrices? Have I done something goofy with the setup of the software?

I’ve pasted the relevant source code below along with the project file (I can’t upload items as a new user).

Thanks!

***** Source Code ****

using System;
using MathNet.Numerics.LinearAlgebra;
using System.Diagnostics;

namespace Copula
{
    class Program
    {
        static void Main(string[] args)
        {
            Console.WriteLine("Parsing matrix dimensions from input parameters.");
            //int n_rows = Int32.Parse(args[0]);
            //int n_columns = Int32.Parse(args[1]);
            int n_columns = 500;
            int n_rows = 64000;
            Console.WriteLine("Generating Random matrix wtih dimensions " + n_rows + " rows and " + n_columns + " columns.");
        var stop_watch = Stopwatch.StartNew();
        var time_series_matrix = GenerateRandomMatrix(n_rows, n_columns);
        stop_watch.Stop();
        Console.Write("Took " + stop_watch.Elapsed + "\n");

        Console.WriteLine("Performing SVD.");

        stop_watch = Stopwatch.StartNew();
        var ts_svd = time_series_matrix.Svd();
        stop_watch.Stop();
        Console.Write("Took " + stop_watch.Elapsed + "\n");

    }

    static Matrix<double> GenerateRandomMatrix(int n_rows, int n_columns)
    {
        Matrix<double> out_matrix = Matrix<double>.Build.Random(n_rows, n_columns);

        return out_matrix;
    }
   }
}

****** Project File

<Project Sdk="Microsoft.NET.Sdk">

 <PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>netcoreapp3.0</TargetFramework>
</PropertyGroup>

<ItemGroup>
<PackageReference Include="MathNet.Numerics" Version="4.8.1" />
<PackageReference Include="MathNet.Numerics.MKL.Win-x64" Version="2.3.0" />
<PackageReference Include="Meta.Numerics" Version="4.0.7" />
</ItemGroup>

</Project>