getMatrix(N) matmultBenchmark(N, n, trim=0.1) matmultBenchmarkgputools(N, n, trim=0.1) qrBenchmark(N, n, trim=0.1) qrBenchmarkgputools(N, n, trim=0.1) svdBenchmark(N, n, trim=0.1)
luBenchmark(N, n, trim=0.1) luBenchmarkgputools(N, n, trim=0.1)mean estimationgetMatrix provides a square matrix of the given dimension. matmultBenchmark times the cost of multiplying a matrix of the
given size with itself, repeated as specified and returns the trimmed
mean of the elapsed times. matmultBenchmarkgputools does the
same using the gputools and packages.
qrBenchmark times the cost of a QR decomposition of a matrix of
the given size, repeated as specified and returns the trimmed mean of
the elapsed times. qrBenchmarkgputools does the same using the
gputools packages.
svdBenchmark times the cost of a Singular Value Decomposition
(SVD) of a matrix of the given size, repeated as specified and returns
the trimmed mean of the elapsed times.
luBenchmark times the cost of a LU Decomposition of a matrix of
the given size, repeated as specified and returns the trimmed mean of
the elapsed times. luBenchmarkgputools does the same using the
gputools package.