Open Access

Modern safety-critical embedded applications like autonomous driving need to be fail-operational. At the same time, high performance and low power consumption are demanded. A common way to achieve this is the use of heterogeneous multi-cores. When applied to such systems, prevalent fault tolerance mechanisms suffer from some disadvantages: Some (e.g. triple modular redundancy) require a substantial amount of duplication, resulting in high hardware costs and power consumption. Others (e.g. lockstep) require supplementary checkpointing mechanisms to recover from errors. Further approaches (e.g. software-based process-level redundancy) cannot handle the indeterminism introduced by multithreaded execution. This paper presents a novel approach for fail-operational systems using hardware transactional memory, which can also be used for embedded systems running heterogeneous multi-cores. Each thread is automatically split into transactions, which then execute redundantly. The hardware transactional memory is extended to support multiple versions, which allows the reproduction of atomic operations and recovery in case of an error. In our FPGA-based evaluation, we executed the PARSEC benchmark suite with fault tolerance on 12 cores.

Background Lymph node staging of ductal adenocarcinoma of the pancreatic head (PDAC) by cross-sectional imaging is limited. The aim of this study was to determine the diagnostic accuracy of expanded criteria in nodal staging in PDAC patients. Methods Sixty-six patients with histologically confirmed PDAC that underwent primary surgery were included in this retrospective IRB-approved study. Cross-sectional imaging studies (CT and/or MRI) were evaluated by a radiologist blinded to histopathology. Number and size of lymph nodes were measured (short-axis diameter) and characterized in terms of expanded morphological criteria of border contour (spiculated, lobulated, and indistinct) and texture (homogeneous or inhomogeneous). Sensitivities and specificities were calculated with histopathology as a reference standard. Results Forty-eight of 66 patients (80%) had histologically confirmed lymph node metastases (pN+). Sensitivity, specificity, and Youden’s Index for the criterion “size” were 44.2%, 82.4%, and 0.27; for “inhomogeneous signal intensity” 25.6%, 94.1%, and 0.20; and for “border contour” 62.7%, 52.9%, and 0.16, respectively. There was a significant association between the number of visible lymph nodes on preoperative CT and lymph node involvement (pN+, p = 0.031). Conclusion Lymph node staging in PDAC is mainly limited due to low sensitivity for detection of metastatic disease. Using expanded morphological criteria instead of size did not improve regional nodal staging due to sensitivity remaining low. Combining specific criteria yields improved sensitivity with specificity and PPV remaining high.