Related papers: Scalable Reliability Modelling of RAID Storage Sub…
The paper is devoted to the problem of erasure coding in distributed storage. We consider a model of storage that assumes that nodes are organized into equally sized groups, called racks, that within each group the nodes can communicate…
While reduction in feature size makes computation cheaper in terms of latency, area, and power consumption, performance of emerging data-intensive applications is determined by data movement. These trends have introduced the concept of…
Embedded systems in safety-critical environments are continuously required to deliver more performance and functionality, while expected to provide verified safety guarantees. Nonetheless, platform-wide software verification (required for…
In-memory (transactional) data stores are recognized as a first-class data management technology for cloud platforms, thanks to their ability to match the elasticity requirements imposed by the pay-as-you-go cost model. On the other hand,…
Reliability has taken centre stage in the development of high-performance computing processors. A Surge of interest is noticeable in recent times in formulating fault and failure models, understanding failure mechanism and strategizing…
Existing compact models for memristive devices (including RRAM and CBRAM) all suffer from issues related to mathematical ill-posedness and/or improper implementation. This limits their value for simulation and design and in some cases,…
Polymer-assisted ion transport underpins both energy storage technologies and emerging neuromorphic computing devices. Efficient modeling of ion migration is essential for understanding the performance of batteries and memristors, but it…
The first step in statistical reliability studies of coherent systems is the estimation of the reliability of each system component. For the cases of parallel and series systems the literature is abundant. It seems that the present paper is…
In the ever-shifting landscape of software engineering, we recognize the need for adaptation and evolution to maintain system dependability. As each software iteration potentially introduces new challenges, from unforeseen bugs to…
Reliability is a fundamental challenge in operating large-scale machine learning (ML) infrastructures, particularly as the scale of ML models and training clusters continues to grow. Despite decades of research on infrastructure failures,…
Many large-scale software systems demonstrate metastable failures. In this class of failures, a stressor such as a temporary spike in workload causes the system performance to drop and, subsequently, the system performance continues to…
Solid-state storage architectures based on NAND or emerging memory devices (SSD), are fundamentally architected and optimized for both reliability and performance. Achieving these simultaneous goals requires co-design of memory components…
SRAM-based FPGAs are popular in the aerospace industry for their field programmability and low cost. However, they suffer from cosmic radiation-induced Single Event Upsets (SEUs). Triple Modular Redundancy (TMR) is a well-known technique to…
Recent approaches to distributed model fitting rely heavily on consensus ADMM, where each node solves small sub-problems using only local data. We propose iterative methods that solve {\em global} sub-problems over an entire distributed…
Physical and cloud storage services are well-served by functioning and reliable high-volume storage systems. Recent observations point to hard disk reliability as one of the most pressing reliability issues in data centers containing…
This initial version of this document was written back in 2014 for the sole purpose of providing fundamentals of reliability theory as well as to identify the theoretical types of machinery for the prediction of durability/availability of…
Large reasoning models (LRMs) have exhibited the capacity of enhancing reasoning performance via internal test-time scaling. Building upon this, a promising direction is to further scale test-time compute to unlock even greater reasoning…
Reliability of complex Cyber-Physical Systems is necessary to guarantee availability and/or safety of the provided services. Diverse and complex fault tolerance policies are adopted to enhance reliability, that include a varied mix of…
We have built PRISM, a "Probabilistic Regression Instrument for Simulating Models". PRISM uses the Bayes linear approach and history matching to construct an approximation ('emulator') of any given model, by combining limited model…
Software reliability estimation is one of the most active areas of research in software testing. Since time between failures (TBF) has often been challenging to record, software testing data are commonly recorded as test-case-wise in a…