Parallel Multithread Analysis of Extremely Large Simulation Traces

With the explosion in the size of off-the-shelf integrated circuits and the advent of novel techniques related to failure modes, commercial Automatic Test Pattern Generator and fault simulation engines are often insufficient to measure the coverage of particular metrics. Consequently, a general working framework consists of storing simulation traces during the analysis phase and collecting test statistics from post-processing. Unfortunately, typical simulation traces can be hundreds of gigabytes long, and their analysis can require several days, even on large and powerful computational servers. In this paper, we propose a set of strategies to mitigate the evaluation time and the memory needed to analyze huge dump files stored in the standard Value Change Dump format. We concentrate on burn-in-related metrics that current commercial fault simulators and Automatic Test Pattern Generators cannot evaluate. We show how to divide the analysis process into several concurrent pipeline stages. We revise the logic process of each stage and all principal intermediate data structures, to adopt smart parallelization with very low contention and extremely low overhead. We exploit several low-level optimizations from modern programming techniques to reduce computation time and balance the different pipeline phases. We analyze simulation traces up to almost 250 GBytes computing different testing metrics. Overall, we can keep under control the memory usage, and we show time improvements of over two orders of magnitude compared to previously adopted state-of-the-art tools

A novel putative interactor for the low density lipoprotein receptor cytoplasmic domain

Familial hypercholesterolemia (FH) is a genetic disease mainly caused by mutations in the low density lipoprotein receptor (LDLLDLLDL-R) gene. However, FH-like phenotypes may also arise from mutations occurring in other genes, the products of which normally interact with the LDLLDLLDL receptor. Although several FH-associated proteins have been discovered, many FH-like phenotypes cannot be linked to mutations in already characterized genes, suggesting the existence of other genes still to be identified, the mutations of which may be directly linked to the FH disorder. In order to identify new putative LDLLDLLDLr interactors possibly involved in its internalization and/or sorting, the cytoplasmic tail of the receptor was used as \u2018bait\u2019 in a two-hybrid assay. We identified an 85-amino acid protein able to bind the LDLLDLLDLr intracellular domain through the last 14 C C-terminal amino acids. The novel protein is probably derived from the translation of an alternative open reading frame of the human MT2A gene

Accelerated Analysis of Simulation Dumps through Parallelization on Multicore Architectures

With the explosion of off-the-shelf SoCs in terms of size and the advent of novel techniques related to failure modes, commercial ATPG and fault simulation engines can often be insufficient to measure the coverage of very specific metrics. In these cases, many researchers firstly store the simulation trace during the analysis phase. Then, they collect the desired statistics during a post-processing step. In this framework, the so-called Value Change Dump (VCD) is a very commonly used file format to record simulation traces. The target of this paper is twofold. From the one hand, we illustrate some Burn-In (BI) related metrics which cannot be evaluated by current commercial fault simulators and ATPG engines. These metrics are indeed based on a post-processing analysis of memory dumps in VCD format. From the other hand, we mitigate the evaluation time and the memory required to analyze huge VCD files by exploiting optimization techniques coming from modern programming features and smart parallelization. Adopting this strategy, we can analyze simulation dumps of more than 250 GBytes in less than one hour, showing improvements of two orders of magnitude over previous tools, with a consequent higher scalability and testability power

A novel loss of function mutation of PCSK9 gene in white subjects with low-plasma low-density lipoprotein cholesterol.

Abstract OBJECTIVES: The PCSK9 gene, encoding a pro-protein convertase involved in posttranslational degradation of low-density lipoprotein receptor, has emerged as a key regulator of plasma low-density lipoprotein cholesterol. In African-Americans two nonsense mutations resulting in loss of function of PCSK9 are associated with a 30% to 40% reduction of plasma low-density lipoprotein cholesterol. The aim of this study was to assess whether loss of function mutations of PCSK9 were a cause of familial hypobetalipoproteinemia and a determinant of low-plasma low-density lipoprotein cholesterol in whites. METHODS AND RESULTS: We sequenced PCSK9 gene in 18 familial hypobetalipoproteinemia subjects and in 102 hypocholesterolemic blood donors who were negative for APOB gene mutations known to cause familial hypobetalipoproteinemia. The PCSK9 gene variants found in these 2 groups were screened in 42 subjects in the lowest (95th) percentile, and 100 with the average plasma cholesterol derived from general population. In one familial hypobetalipoproteinemia kindred and in 2 hypocholesterolemic blood donors we found a novel PCSK9 mutation in exon 1 (c.202delG) resulting in a truncated peptide (Ala68fsLeu82X). Two familial hypobetalipoproteinemia subjects and 4 hypocholesterolemic blood donors were carriers of the R46L substitution previously reported to be associated with reduced low-density lipoprotein cholesterol as well as other rare amino acid changes (T77I, V114A, A522T and P616L) not found in the other groups examined. CONCLUSIONS: We discovered a novel inactivating mutation as well as some rare nonconservative amino acid substitutions of PCSK9 in white hypocholesterolemic individuals