ESWEEK

Over the last five years Deep Neural Nets have offered more accurate solutions to many problems in speech recognition, and computer vision, and these solutions have surpassed a threshold of acceptability for many applications. As a result, Deep Neural ...

Streaming applications are often modeled with Synchronous data flow graphs (SDFGs). A proper analysis of the models is helpful to predict the performance of a system. In this paper, we focus on the throughput analysis of memory-constrained SDFGs (MC ...

This paper proposes to improve read performance of LDPC based flash memory by exploiting process variation (PV). The work includes three parts. First, a block grouping approach is proposed to classify the flash blocks based on their reliability. Second, ...

Studies have shown memory and computational needs vary independently across applications. Recent work has explored using hybrid memory technology (SRAM+NVM) in on-chip memories of multicore processors (CMPs) to support the varied needs of diverse ...

Over the past few years, NAND flash-based Solid State Drives (SSDs) are progressively replacing Hard Disk Drives (HDDs) in various applications ranging from personal computers to large-scale storage servers, due to their high performance and low power ...

Advances in computing steadily erode computer security at its foundation, calling for fundamental innovations to strengthen the weakening cryptographic primitives and security protocols. At the same time, the emergence of new computing paradigms, such ...

Lattice-based cryptography is a promising family of post quantum algorithms. Contrary to other approaches, lattice-based primitives are extremely versatile and allow the realisation of several essential cryptographic primitives, such as encryption and ...

Research on physical attacks on lattice-based cryptography has seen some progress in recent years and first attacks and countermeasures have been described. In this work, we perform an exhaustive literature review on fault attacks on lattice-based ...

In the past decade, the number of reported security attacks exploiting unchecked input firmware values has been on the rise. To address this concerning trend, this work proposes a novel detection framework, called DOVE, capable of identifying unlikely ...

Unauthorized hardware or firmware modifications, known as trojans, can steal information, drain the battery, or damage IoT devices. This paper presents a stand-off self-referencing technique for detecting unauthorized activity. The proposed technique ...

System-level thermal management techniques normally map applications on non-adjacent cores to guarantee the safe temperature in many-core systems, while the communication efficiency will be oppositely affected by long-distance data transmission over ...

In this work, we explore a security reference monitor (RM) design which borrows from the Flask security architecture. Our RM design goal is to achieve complete mediation by checking and verifying the authority and the authenticity of every access to ...

Originally developed for purely functional verification of software, native or host compiled simulation [6] has gained momentum, thanks to its considerable speedup compared to instruction set simulation (ISS). To obtain a performance model of the ...

High Efficiency Video Coding (HEVC) provides high efficiency at the cost of increased computational complexity followed by increased power consumption and temperature of current Multi-Processor Systems-on-Chip (MPSoCs). In this paper, we propose a ...

Battery and energy management methodologies such as automotive climate controls have been proposed to address the design challenges of driving range and battery lifetime in Electric Vehicles (EV). However, driving behavior estimation is a major factor ...

Recently, FPGAs have been widely used in the implementation of hardware accelerators for Convolutional Neural Networks (CNN), especially on mobile and embedded devices. However, most of these existing accelerators are designed with the same concept as ...

As manufacturing processes scale to smaller feature sizes and processors become more complex, it is becoming challenging to have fabricated devices that operate according to their specification in the first place: yield losses are mounting [3].

Deployment of IoT devices for smart buildings and homes will offer a high level of comfortability with increased energy efficiency; but can also introduce potential cyber-attacks such as network intrusions via linked IoT devices. Due to the low-power ...

Harvested energy is intrinsically unstable and program execution will be interrupted frequently. To solve this problem, nonvolatile processor (NVP) is proposed because it can back up volatile state before the system energy is depleted. However, the ...

The amount of data generated and collected across computing platforms every day is not only enormous, but growing at an exponential rate. Advanced data analytics and machine-learning techniques have become increasingly essential to analyze and extract ...

With increasing resolutions the volume of data generated by image processing applications is escalating dramatically. When coupled with real-time performance requirements, reducing energy consumption for such a large volume of data is proving ...

The world's appetite for abundant-data computing, where a massive amount of structured and unstructured data is analyzed, has increased dramatically. The computational demands of these applications, such as deep learning, far exceed the capabilities of ...

Approximate computing aims to expose and exploit quality vs. efficiency tradeoffs to enable ever-more demanding applications on energy-constrained devices such as smartphones, or IoT devices. This paper makes the case for arbitrary quantization as a ...

The superior controllability of the cerebellum has motivated extensive interest in the development of computational cerebellar models. Many models have been applied to the motor control and image stabilization in robots. Often computationally complex, ...