Performance Analysis of the SHA-3 Candidates on Exotic Multi-core Architectures

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Embedded memories occupy an increasingly dominant part of the area and power budgets of modern systems-on-chips (SoCs). Multi-ported embedded memories, commonly used by media SoCs and graphical processing units, occupy even more area and consume higher pow ...

Verification and testing of hardware heavily relies on cycle-accurate simulation of RTL. As single-processor performance is growing only slowly, conventional, single-threaded RTL simulation is becoming impractical for increasingly complex chip designs and ...

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

Current cryptographic solutions will become obsolete with the arrival of large-scale universal quantum computers. As a result, the National Institute of Standards and Technology supervises a post-quantum standardization process which involves evaluating ca ...

Detecting digital face manipulation in images and video has attracted extensive attention due to the potential risk to public trust. To counteract the malicious usage of such techniques, deep learning-based deepfake detection methods have been employed and ...

Embedded systems confront two opposite goals: low-power operation and high performance. The current trend to reach these goals is toward heterogeneous platforms, including multi-core architectures with heterogeneous cores and hardware accelerators. The lat ...

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

The demise of Moore's Law and Dennard scaling has resulted in diminishing performance gains for general-purpose processors, and so has prompted a surge in academic and commercial interest for hardware accelerators. Specialized hardware has already redefine ...

Dataflow programming is a methodology that enables the development of high-level, parametric programs that are independent of the underlying platform. This approach is particularly useful for heterogeneous platforms, as it eliminates the need to rewrite ap ...

Modern data management systems aim to provide both cutting-edge functionality and hardware efficiency. With the advent of AI-driven data processing and the post-Moore Law era, traditional memory-bound scale-up data management operations face scalability ch ...

The detection of digital face manipulation in video has attracted extensive attention due to the increased risk to public trust. To counteract the malicious usage of such techniques, deep learning-based deepfake detection methods have been developed and ha ...

Side-channel disassembly attacks recover CPU instructions from power or electromagnetic side-channel traces measured during code execution. These attacks typically rely on physical access, proximity to the victim device, and high sampling rate measuring in ...

The spectral decomposition of cryptography into its life-giving components yields an interlaced network of tangential and orthogonal disciplines that are nonetheless invariably grounded by the same denominator: their implementation on commodity computing p ...

Acoustic emission (AE) monitoring is commonly used to inspect the health of a structure continuously. During fracture processes elastic waves of AE are created and emitted, and sensors can capture these waves. The acquired signals can be processed to track ...

To answer the growing demand for hardware acceleration, Amazon, Microsoft, and many other major cloud service providers have included field-programmable gate arrays (FPGAs) in their datacenters. However, researchers have shown that cloud FPGAs, when shared ...

Modern hardware is increasingly complex, requiring increasing effort to understand in order to carefully engineer systems for optimal performance and effective utilization. Moreover, established design principles and assumptions are not portable to modern ...

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

Compute memories are memory arrays augmented with dedicated logic to support arithmetic. They support the efficient execution of data-centric computing patterns, such as those characterizing Artificial Intelligence (AI) algorithms. These architectures can ...

Acoustic emission (AE) monitoring is a useful technique to monitor the health of a structure continuously, helping to prevent potential failure. AE are elastic waves produced and emitted during fracture processes inside a material and are recorded by senso ...

The miniaturization of integrated circuits (ICs) and their higher performance and energy efficiency, combined with new machine learning algorithms and applications, have paved the way to intelligent, interconnected edge devices. In the medical domain, they ...

Performance Analysis of the SHA-3 Candidates on Exotic Multi-core Architectures

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Multi-Ported GC-eDRAM Bitcell with Dynamic Port Configuration and Refresh Mechanism

Highly Parallel RTL Simulation

EdgeAI-Aware Design of In-Memory Computing Architectures

Side-channel analysis of isogeny-based key encapsulation mechanisms and hash-based digital signatures

Assessment framework for deepfake detection in real-world situations

Acceleration of Control Intensive Applications on Coarse-Grained Reconfigurable Arrays for Embedded Systems

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

Building Chips Faster: Hardware-Compiler Co-Design for Accelerated RTL Simulation

Design Space Exploration for Partitioning Dataflow Program on CPU-GPU Heterogeneous System

Post-Moore's Law Fusion: High-Bandwidth Memory, Accelerators, and Native Half-Precision Processing for CPU-Local Analytics

Impact of Video Processing Operations in Deepfake Detection

Instruction-Level Power Side-Channel Leakage Evaluation of Soft-Core CPUs on Shared FPGAs

Green Cryptography and Other Optimisations

Automatic and high-precision microseismic monitoring of progressive failure prior, during, and after tunnel excavation

Temperature Impact on Remote Power Side-Channel Attacks on Shared FPGAs

Chaosity: Understanding Contemporary NUMA-architectures

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

Overflow-free compute memories for edge AI acceleration

Automatic and high-precision acoustic emission-based structural health monitoring of concrete structures

Exploring brain-inspired multi-core heterogeneous hardware templates for low-power biomedical embedded systems