Approaches to multiprocessor error recovery using an on-chip interconnect subsystem

For future multicores, a dedicated interconnect subsystem for on-chip monitors was found to be highly beneficial in terms of scalability, performance and area. In this thesis, such a monitor network (MNoC) is used for multicores to support selective error identification and recovery and maintain target chip reliability in the context of dynamic voltage and frequency scaling (DVFS). A selective shared memory multiprocessor recovery is performed using MNoC in which, when an error is detected, only the group of processors sharing an application with the affected processors are recovered. Although the use of DVFS in contemporary multicores provides significant protection from unpredictable thermal events, a potential side effect can be an increased processor exposure to soft errors. To address this issue, a flexible fault prevention and recovery mechanism has been developed to selectively enable a small amount of per-core dual modular redundancy (DMR) in response to increased vulnerability, as measured by the processor architectural vulnerability factor (AVF). Our new algorithm for DMR deployment aims to provide a stable effective soft error rate (SER) by using DMR in response to DVFS caused by thermal events. The algorithm is implemented in real-time on the multicore using MNoC and controller which evaluates thermal information and multicore performance statistics in addition to error information. DVFS experiments with a multicore simulator using standard benchmarks show an average 6% improvement in overall power consumption and a stable SER by using selective DMR versus continuous DMR deployment

A Screening Test for Disclosed Vulnerabilities in FOSS Components

Free and Open Source Software (FOSS) components are ubiquitous in both proprietary and open source applications. Each time a vulnerability is disclosed in a FOSS component, a software vendor using this an application must decide whether to update the FOSS component, patch the application itself, or just do nothing as the vulnerability is not applicable to the older version of the FOSS component used. This is particularly challenging for enterprise software vendors that consume thousands of FOSS components and offer more than a decade of support and security fixes for their applications. Moreover, customers expect vendors to react quickly on disclosed vulnerabilities—in case of widely discussed vulnerabilities such as Heartbleed, within hours. To address this challenge, we propose a screening test: a novel, automatic method based on thin slicing, for estimating quickly whether a given vulnerability is present in a consumed FOSS component by looking across its entire repository. We show that our screening test scales to large open source projects (e.g., Apache Tomcat, Spring Framework, Jenkins) that are routinely used by large software vendors, scanning thousands of commits and hundred thousands lines of code in a matter of minutes. Further, we provide insights on the empirical probability that, on the above mentioned projects, a potentially vulnerable component might not actually be vulnerable after all