Memory-Aware Genetic Algorithms for Task Mapping on Hard Real-Time Networks-on-Chip

The problem of mapping hard real-time tasks onto networks-on-chip has previously been successfully addressed by genetic algorithms. However, none of the existing problem formulations consider memory constraints. State-of-the-art genetic mappers are therefore able to find fully-schedulable mappings which are incompatible with the memory limitations of realistic platforms. In this paper, we extend the problem formulation and devise a memory architecture, in the form of private local memories. We then propose three memory models of increasing complexity and realism, and evaluate the impact these additional constraints pose to the genetic search. We conduct extensive experiments using tasks and communications from a realistic benchmark application, and compare the proposed approach against a state-of-the-art baseline mapper

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead