We present a new algorithm for numerical computation of large eigenvalues and associated eigenfunctions of the Dirichlet Laplacian in a smooth, star-shaped2. Conventional boundary-based methods require a root search in eigenfrequency k, hence take O.N 3 / effort per eigenpair found, where/ is the number of unknowns required to discretize the boundary. Our method is O.N / faster, achieved by linearizing with respect to k the spectrum of a weighted interior Neumann-to-Dirichlet (NtD) operator for the Helmholtz equation. Approximations y k j to the square roots k j of all O.N / eigenvalues lying in OEk ; k, where D O.1/, are found with O.N 3 / effort. We prove an error estimatewith C independent of k. We present a higher-order variant with eigenvalue error scaling empirically as O. 5 / and eigenfunction error as O. 3 /, the former improving upon the "scaling method" of Vergini and Saraceno. For planar domains (d D 2), with an assumption of absence of spectral concentration, we also prove rigorous error bounds that are close to those numerically observed. For d D 2 we compute robustly the spectrum of the NtD operator via potential theory, Nyström discretization, and the Cayley transform. At high frequencies (400 wavelengths across), with eigenfrequency relative error 10 10 , we show that the method is 10 3 times faster than standard ones based upon a root search.