Related papers: IPU: Flexible Hardware Introspection Units
In this paper, we propose StruM, a novel structured mixed-precision-based deep learning inference method, co-designed with its associated hardware accelerator (DPU), to address the escalating computational and memory demands of deep…
Rising complexity of in-vehicle electronics is enabling new capabilities like autonomous driving and active safety. However, rising automation also increases risk of security threats which is compounded by lack of in-built security measures…
Recent years have seen an exponential rise in complex software-driven functionality in vehicles, leading to a rising number of electronic control units (ECUs), network capabilities, and interfaces. These expanded capabilities also bring-in…
In this paper, phasor measurement unit (PMU) placement for power grid state estimation under different degrees of observability is studied. Observability degree is the depth of the buses' reachability by the placed PMUs and thus constitutes…
Deep learning model design, development, and debugging is a process driven by best practices, guidelines, trial-and-error, and the personal experiences of model developers. At multiple stages of this process, performance and internal model…
Understanding the internals of Integrated Circuits (ICs), referred to as Hardware Reverse Engineering (HRE), is of interest to both legitimate and malicious parties. HRE is a complex process in which semi-automated steps are interwoven with…
Processing large-scale graph datasets is computationally intensive and time-consuming. Processor-centric CPU and GPU architectures, commonly used for graph applications, often face bottlenecks caused by extensive data movement between the…
This paper presents a detailed evaluation of the efficiency of software-only techniques to mitigate SEU and SET in microprocessors. A set of well-known rules is presented and implemented automatically to transform an unprotected program…
The deployment of machine learning (ML) models on microcontrollers (MCUs) is constrained by strict energy, latency, and memory requirements, particularly in battery-operated and real-time edge devices. While software-level optimizations…
Data movement between memory and processors is a major bottleneck in modern computing systems. The processing-in-memory (PIM) paradigm aims to alleviate this bottleneck by performing computation inside memory chips. Real PIM hardware (e.g.,…
Machine learning applications are computationally demanding and power intensive. Hardware acceleration of these software tools is a natural step being explored using various technologies. A recurrent processing unit (RPU) is fast and…
Timely recognition of voltage instability is crucial to allow for effective control and protection interventions. Phasor measurements units (PMUs) can be utilized to provide high sampling rate time-synchronized voltage and current phasors…
In the context of hardware trust and assurance, reverse engineering has been often considered as an illegal action. Generally speaking, reverse engineering aims to retrieve information from a product, i.e., integrated circuits (ICs) and…
Intellectual property (IP) piracy has become a non-negligible problem as the integrated circuit (IC) production supply chain is becoming increasingly globalized and separated that enables attacks by potentially untrusted attackers. Logic…
Due to the emergence of embedded applications in image and video processing, communication and cryptography, improvement of pictorial information for better human perception like deblurring, denoising in several fields such as satellite…
GPUs are the dominant platform for many important applications today including deep learning, accelerated computing, and scientific simulation. However, as the complexity of both applications and hardware increases, GPU chip manufacturers…
Cloud computing systems fail in complex and unexpected ways due to unexpected combinations of events and interactions between hardware and software components. Fault injection is an effective means to bring out these failures in a…
Emulating firmware for microcontrollers is challenging due to the tight coupling between the hardware and firmware. This has greatly impeded the application of dynamic analysis tools to firmware analysis. The state-of-the-art work…
This paper explores Google's Edge TPU for implementing a practical network intrusion detection system (NIDS) at the edge of IoT, based on a deep learning approach. While there are a significant number of related works that explore machine…
Very deep submicron and nanometer technologies have increased notably integrated circuit (IC) sensitiveness to radiation. Soft errors are currently appearing into ICs working at earth surface. Hardened circuits are currently required in…