Parallel Recursive State Compression for Free

This paper focuses on reducing memory usage in enumerative model checking, while maintaining the multi-core scalability obtained in earlier work. We present a tree-based multi-core compression method, which works by leveraging sharing among sub-vectors of state vectors. An algorithmic analysis of both worst-case and optimal compression ratios shows the potential to compress even large states to a small constant on average (8 bytes). Our experiments demonstrate that this holds up in practice: the median compression ratio of 279 measured experiments is within 17% of the optimum for tree compression, and five times better than the median compression ratio of SPIN's COLLAPSE compression. Our algorithms are implemented in the LTSmin tool, and our experiments show that for model checking, multi-core tree compression pays its own way: it comes virtually without overhead compared to the fastest hash table-based methods.Comment: 19 page

Variations on Multi-Core Nested Depth-First Search

Recently, two new parallel algorithms for on-the-fly model checking of LTL properties were presented at the same conference: Automated Technology for Verification and Analysis, 2011. Both approaches extend Swarmed NDFS, which runs several sequential NDFS instances in parallel. While parallel random search already speeds up detection of bugs, the workers must share some global information in order to speed up full verification of correct models. The two algorithms differ considerably in the global information shared between workers, and in the way they synchronize. Here, we provide a thorough experimental comparison between the two algorithms, by measuring the runtime of their implementations on a multi-core machine. Both algorithms were implemented in the same framework of the model checker LTSmin, using similar optimizations, and have been subjected to the full BEEM model database. Because both algorithms have complementary advantages, we constructed an algorithm that combines both ideas. This combination clearly has an improved speedup. We also compare the results with the alternative parallel algorithm for accepting cycle detection OWCTY-MAP. Finally, we study a simple statistical model for input models that do contain accepting cycles. The goal is to distinguish the speedup due to parallel random search from the speedup that can be attributed to clever work sharing schemes.Comment: In Proceedings PDMC 2011, arXiv:1111.006

Percutaneous coronary intervention for non ST-elevation acute coronary syndromes: which, when and how?

Contains fulltext : 97210.pdf (publisher's version ) (Closed access)The presentation of patients with suspected non ST-elevation acute coronary syndromes is quite diverse. Therefore, the diagnostic workup and choice of treatment may vary accordingly. Major issues regarding the evaluation are the likelihood of the diagnosis and the risk for adverse events. These factors should guide the choice of diagnostic test. Patients with increased risk for ischemic events and patients with recurrent ischemia are most likely to benefit from revascularization. In addition, when percutaneous coronary intervention is considered, evidence suggests that sufficient time should be allowed for pharmacologic stabilization, reducing the possibility of periprocedurally inflicted myocardial infarction. However, postponement of intervention may lead to an increase of new spontaneous events, and high-risk patients should apply for revascularization soon after pharmacologic stabilization. The extent of revascularization performed by percutaneous coronary intervention depends predominantly on patient characteristics and anatomy but should be limited to flow-obstructive lesions. In conclusion, patients presenting with non-ST elevation acute coronary syndromes constitute a very diverse population; diagnostic workup, treatment, and the timing of a possible intervention should be tailored individually

The Biochemical Aspects of a Non-ST-Segment Elevation Acute Coronary Syndrome

Contains fulltext : 109713.pdf (publisher's version ) (Open Access)The clinical course of an acute coronary syndrome can vary from relatively benign to potentially fatal. The biomarkers of myocardial necrosis relate to the amount of myocardial damage and are closely linked to a patient's prognosis. They are measured to help guide management decisions. Recent interest in myocardial neurohumoral mechanisms has identified the natriuretic peptides as strong prognostic biomarkers following an ischemic event. During an acute event they provide information regarding the area of myocardium at risk. The biomarkers of inflammation, such as C-reactive protein, are related to both the development of atherosclerosis and the risk of acute ischemic events. The mechanism characterizing the pathophysiology of the syndrome is represented by these cardiac biomarkers. Assessing combinations of pathobiologically diverse biomarkers may provide a better risk evaluation method and further dictate subsequent therapy