Tracing Fault Effects in FPGA Systems

The paper presents the extent of fault effects in FPGA based systems and concentrates on transient faults (induced by single event upsets – SEUs) within the configuration memory of FPGA. An original method of detailed analysis of fault effect propagation is presented. It is targeted at microprocessor based FPGA systems using the developed fault injection technique. The fault injection is performed at HDL description level of the microprocessor using special simulators and developed supplementary programs. The proposed methodology is illustrated for soft PicoBlaze microprocessor running 3 programs. The presented results reveal some problems with fault handling at the software level.

Functional Testing of Processor Cores in FPGA-Based Applications

Embedded processor cores, which are widely used in SRAM-based FPGA applications, are candidates for SEU (Single Event Upset)-induced faults and need to be tested occasionally during system exploitation. Verifying a processor core is a difficult task, due to its complexity and the lack of user knowledge about the core-implementation details. In user applications, processor cores are normally tested by executing some kind of functional test in which the individual processor's instructions are tested with a set of deterministic test patterns, and the results are then compared with the stored reference values. For practical reasons the number of test patterns and corresponding results is usually small, which inherently leads to low fault coverage. In this paper we develop a concept that combines the whole instruction-set test into a compact test sequence, which can then be repeated with different input test patterns. This improves the fault coverage considerably with no additional memory requirements

Statin use in cancer patients with acute myocardial infarction and its impact on long-term mortality

Statin use and its impact on long-term clinical outcomes in active cancer patients following acute myocardial infarction (MI) remains insufficiently elucidated. Of the 1011 consecutive acute MI patients treated invasively between 2012 and 2017, cancer was identified in 134 (13.3%) subjects. All patients were observed within a median follow-up of 69.2 (37.8–79.9) months. On discharge, statins were prescribed less frequently in MI patients with cancer as compared to the non-cancer MI population (79.9% vs. 91.4%, p < 0.001). The most common statin in both groups was atorvastatin. The long-term mortality was higher in MI patients not treated vs. those treated with statins, both in non-cancer (29.5%/year vs. 6.7%/year, p < 0.001) and cancer groups (53.9%/year vs. 24.9%/year, p < 0.05), respectively. Patient’s age (hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.03–1.05, p < 0.001, per year), an active cancer (HR 2.42, 95% CI 1.89–3.11, p < 0.001), hemoglobin level (HR 1.14, 95% CI 1.09–1.20, p < 0.001, per 1 g/dL decrease), and no statin on discharge (HR 2.13, 95% CI 1.61–2.78, p < 0.001) independently increased long-term mortality. In MI patients, simultaneous diagnosis of an active cancer was associated with less frequently prescribed statins on discharge. Irrespective of cancer diagnosis, no statin use was found as an independent predictor of increased long-term mortality