How can the C++ Eigen library perform better than specialized vendor libraries?
I was looking over the performance benchmarks: http://eigen.tuxfamily.org/index.php?title=Benchmark
I could not help but notice that eigen appears to consistently outperform all the specialized vendor libraries. The questions is: how is it possible? One would assume that mkl/goto would use processor specific tuned code, while eigen is rather generic.
Notice this http://download.tuxfamily.org/eigen/btl-results-110323/aat.pdf, essentially a dgemm. For N=1000 Eigen gets roughly 17Gf, MKL only 12Gf
Answer
Eigen has lazy evaluation. From How does Eigen compare to BLAS/LAPACK?:
For operations involving complex expressions, Eigen is inherently faster than any BLAS implementation because it can handle and optimize a whole operation globally -- while BLAS forces the programmer to split complex operations into small steps that match the BLAS fixed-function API, which incurs inefficiency due to introduction of temporaries. See for instance the benchmark result of a Y = aX + bY operation which involves two calls to BLAS level1 routines while Eigen automatically generates a single vectorized loop.
The second chart in the benchmarks is Y = a*X + b*Y, which Eigen was specially designed to handle. It should be no wonder that a library wins at a benchmark it was created for. You'll notice that the more generic benchmarks, like matrix-matrix multiplication, don't show any advantage for Eigen.