Ionizing particles in the atmosphere may strike circuits causing Single Event Upsets (SEU), affecting the output correctness. Critical real-time systems are traditionally custom-designed, featuring redundancy for guaranteeing fault resilience. The ...

Deep neural networks (DNNs) have emerged as an effective solution for many machine learning applications. However, the great success comes with the cost of excessive computation. The Volta graphics processing unit (GPU) from NVIDIA introduced a ...

Fault tolerance, energy management, and quality of service (QoS) are essential aspects for the design of real-time embedded systems. In this work, we focus on exploring methods that can simultaneously address the above three critical issues under standby-...

Nowadays, Electronic Toll Collection (ETC) control systems have been widely adopted to smoothen traffic flow on highways. However, as it is a complex business interaction system, there are inevitably flaws in its control logic process, such as the problem ...

Real-time systems are susceptible to adversarial factors such as faults and attacks, leading to severe consequences. This paper presents an optimal checkpoint scheme to bolster fault resilience in real-time systems, addressing both logical consistency and ...

Approximate Computing Techniques (ACTs) take advantage of resilience computing applications to trade off among output precision, area, power, and performance. ACTs can lead to significant gains at affordable costs when efficiently implemented on Field ...

The increasing use of Machine Learning (ML) components embedded in autonomous systems—so-called Learning-Enabled Systems (LESs)—has resulted in the pressing need to assure their functional safety. As for traditional functional safety, the emerging ...

One of the most difficult data flow errors to detect caused by single-event upsets in space radiation is the Silent Data Corruption (SDC). To solve the problem of multi-bit upsets causing program SDC, an instruction multi-bit SDC vulnerability prediction ...

In artificial intelligence planning, having an explanation of a plan given by a planner is often desirable. The ability to explain various aspects of a synthesized plan to an end user not only brings in trust on the planner but also reveals insights of ...

Read disturb is a circuit-level noise in flash-based Solid-State Drives (SSDs), induced by intensive read requests, which may result in unexpected read errors. The approach of read refresh (RR) is commonly adopted to mitigate its negative effects by ...

In the deep sub-micron region, “spin-transfer torque RAM” (STT-RAM) suffers from “read-disturbance error” (RDE), whereby a read operation disturbs the stored data. Mitigation of RDE requires restore operations, which imposes latency and energy penalties. ...

Multi-Access Edge Computing (MEC) has emerged as a promising new paradigm allowing low latency access to services deployed on edge servers to avert network latencies often encountered in accessing cloud services. A key component of the MEC environment is ...

Modern computer server systems are increasingly managed at a low level by baseboard management controllers (BMCs). BMCs are processors with access to the most critical parts of the platform, below the level of OS or hypervisor, including control over ...

Hardware accelerators are essential to the accommodation of ever-increasing Deep Neural Network (DNN) workloads on the resource-constrained embedded devices. While accelerators facilitate fast and energy-efficient DNN operations, their accuracy is ...

As deep learning algorithms are widely adopted, an increasing number of them are positioned in embedded application domains with strict reliability constraints. The expenditure of significant resources to satisfy performance requirements in deep neural ...

Safety-critical embedded systems may either use specialized hardware or rely on Software-Implemented Hardware Fault Tolerance (SIHFT) to meet soft error resilience requirements. SIHFT has the advantage that it can be used with low-cost, off-the-shelf ...

The growing popularity of convolutional neural networks (CNNs) has led to the search for efficient computational platforms to accelerate CNN training. Resistive random-access memory (ReRAM)-based manycore architectures offer a promising alternative to ...

Garbage collected programming languages, such as Python and C#, have accelerated software development. These modern languages increase productivity and software reliability as they provide high-level data representation and control structures. Modern ...

Time-sensitive Networking (TSN) on Ethernet is a promising communication technology in the automotive and industrial automation industries due to its real-time and high-bandwidth communication capabilities. Time-triggered scheduling and static routing ...

Increased access to space has led to an increase in the usage of commodity processors in radiation environments. These processors are vulnerable to transient faults such as single event upsets that may cause bit-flips in processor components. Caches in ...