An Indictment of Bright Line Tests for Honest Services Mail Fraud

Sparse matrix-matrix multiplication (SpGEMM) is a computational primitive that is widely used in areas ranging from traditional numerical applications to recent big data analysis and machine learning. Although many SpGEMM algorithms have been proposed, hardware specific optimizations for multi- and many-core processors are lacking and a detailed analysis of their performance under various use cases and matrices is not available. We firstly identify and mitigate multiple bottlenecks with memory management and thread scheduling on Intel Xeon Phi (Knights Landing or KNL). Specifically targeting multi- and many-core processors, we develop a hash-table-based algorithm and optimize a heap-based shared-memory SpGEMM algorithm. We examine their performance together with other publicly available codes. Different from the literature, our evaluation also includes use cases that are representative of real graph algorithms, such as multi-source breadth-first search or triangle counting. Our hash-table and heap-based algorithms are showing significant speedups from libraries in the majority of the cases while different algorithms dominate the other scenarios with different matrix size, sparsity, compression factor and operation type. We wrap up in-depth evaluation results and make a recipe to give the best SpGEMM algorithm for target scenario. A critical finding is that hash-table-based SpGEMM gets a significant performance boost if the nonzeros are not required to be sorted within each row of the output matrix

Suppression of spin-torque in current perpendicular to the plane spin-valves by addition of Dy cap layers

We demonstrate that the addition of Dy capping layers in current perpendicular to the plane giant magneto-resistive spin-valves can increase the critical current density beyond which spin-torque induced instabilities are observed by about a factor of three. Current densities as high as 5e7 A/cm2 are measured provided that the electron current flows from the free to the reference layer. While Dy capped samples exhibit nonmagnetic 1/f noise, it is sufficiently small to be unimportant for read head operation at practical data rates.Comment: 13 pages (manuscript form), with 5 figures. Submitted for publicatio