Accelerated coordinate descent is widely used in optimization due to its cheap per-iteration cost and scalability to large-scale problems. Up to a primal-dual transformation, it is also the same as accelerated stochastic gradient descent that is one of the central methods used in machine learning. In this paper, we improve the best known running time of accelerated coordinate descent by a facto...

We investigate the following very simple load-balancing algorithm on the N-cycle (N even) which we call Odd-Even Transposition Balancing (OETB). The edges of the cycle are partitioned into two matchings canonically. A matching defines a single step, the two matchings form a single round. Processors connected by an edge of the matching perfectly balance their loads, and, if there is an excess to...

Trus paper is concerned with the average rUDDing time of Batcher's odd-even merge sort when implemented on a collection of processors. We consider the case where n, the size of the input, is an arbitrary multiple of the number p of processors used. We show that Batcher's odd-even merge (for two sorted lists of length n each) can be implemented to run in time O«nlp)(log(2 + p2 In))) on the avera...

Based on the charge independence hypothesis the properties of V particles are theoretically investigated. It is found that the curious behaviours of these unstable particles are most simply interpreted in terms of the 1}-charge conservation law which directly results from the C. I. hypothesis and suitable isotopic spin assignments to these particles. The topics which are discussed in this paper...

There is a large gap between Zhang’s theoretical bound for the length n of a binary extremal self-dual doublyeven code and what we can construct. The largest n is 136. In order to find examples for larger n a non-trivial automorphism group might be helpful. In the list of known examples extended quadratic residue codes and quadratic double circulant codes have large automorphism groups. But in ...

Dynamic optimization of computer programs can dramatically improve their performance on a variety of applications. This paper presents an efficient infrastructure for dynamic recompilation that can support a wide range of dynamic optimizations including profile-driven optimizations. The infrastructure allows any section of code to be optimized and regenerated on-the-fly, even code for currently...