Domain-specific application analysis for customized instruction identification

With the increasing importance of Application Domain Specific Processor (ADSP) design, a significant challenge is to identify special-purpose operations for implementation as a customized instruction. While many methodologies have been proposed for this purpose, they all work for a single algorithm chosen from the target application domain. Such algorithm-specific approaches are not suitable for designing instruction sets applicable to a whole family of related algorithms. For an entire range of related algorithms, this paper develops a methodology for identifying compound operations, as a basis for designing “domain-specific” Instruction Set Architectures (ISAs) that can efficiently run most of the algorithms in a given domain. Our methodology combines three different static analysis techniques to identify instruction sequences common to several related algorithms: identification of (non-branching) instruction sequences that occur commonly across the algorithms; identification of instruction sequences nested within iterative constructs that are thus executed frequently; and identification of commonly-occurring instruction sequences that span basic blocks. Choosing different combinations of these results enables us to design domain-specific special operations with different desired characteristics, such as performance or suitability as a library function. To demonstrate our approach, case studies are carried out for a family of thirteen string matching algorithms. Finally, the validity of our static analysis results is confirmed through independent dynamic analysis experiments and performance improvement measurements.

A population-specific HTR2B stop codon predisposes to severe impulsivity

Impulsivity, describing action without foresight, is an important feature of several psychiatric diseases, suicidality and violent behaviour. The complex origins of impulsivity hinder identification of the genes influencing it and the diseases with which it is associated. Here we perform exon-focused sequencing of impulsive individuals in a founder population, targeting fourteen genes belonging to the serotonin and dopamine domain. A stop codon in HTR2B was identified that is common (minor allele frequency > 1%) but exclusive to Finnish people. Expression of the gene in the human brain was assessed, as well as the molecular functionality of the stop codon, which was associated with psychiatric diseases marked by impulsivity in both population and family-based analyses. Knockout of Htr2b increased impulsive behaviours in mice, indicative of predictive validity. Our study shows the potential for identifying and tracing effects of rare alleles in complex behavioural phenotypes using founder populations, and indicates a role for HTR2B in impulsivity.