X-Attack 2.0: The Risk of Power Wasters and Satisfiability Don’t-Care Hardware Trojans to Shared Cloud FPGAs

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Machine learning algorithms such as Convolutional Neural Networks (CNNs) are characterized by high robustness towards quantization, supporting small-bitwidth fixed-point arithmetic at inference time with little to no degradation in accuracy. In turn, small ...

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 ...

Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and ...

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

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 ...

The pervasive adoption of field-programmable gate arrays (FPGAs) in both cyber-physical systems and the cloud has raised many security issues. Being integrated circuits, FPGAs are susceptible to fault and power side-channel attacks, which require physical ...

Field-programmable gate arrays (FPGAs) have become critical components in many cloud computing platforms. These devices possess the fine-grained parallelism and specialization needed to accelerate applications ranging from machine learning to networking an ...

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 ...

Cloud computing environments increasingly provision FPGAs because of their fine-grained, highly parallel, and flexible hardware architecture. The availability of FPGAs in the cloud fueled research on the security risks associated with exposing FPGA fabric ...

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 ...

We identified that in modern commercial FPGAs, routing signals from the general interconnect to the configurable logic blocks (CLBs) through a very sparse input interconnect block (IIB) represents a significant runtime bottleneck. This is despite academic ...

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 ...

With Moore's law coming to an end, increasingly more hope is being put in specialized hardware implemented on reconfigurable architectures such as Field-Programmable Gate Arrays (FPGAs). Yet, it is often neglected that these architectures themselves experi ...

By supporting the access of multiple memory words at the same time, Bit-line Computing (BC) architectures allow the parallel execution of bit-wise operations in-memory. At the array periphery, arithmetic operations are then derived with little additional o ...

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 ...

Predictive models based on machine learning (ML) offer a compelling promise: bringing clarity and structure to complex natural and social environments. However, the use of ML poses substantial risks related to the privacy of their training data as well as ...

Owing to the advancements in the area of power electronics, efficient and flexible ac to dc conversion is made possible, bringing back into focus the idea of the dc power transmission at various voltage levels. Several technical and economical factors advo ...

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 ...

The invention relates to a method for operating a power switching device, particularly a wide bandgap power switching device, in a power application, particularly in a converter, comprising the steps of:- checking (S2) a transient voltage of or related to ...

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 ...

X-Attack 2.0: The Risk of Power Wasters and Satisfiability Don’t-Care Hardware Trojans to Shared Cloud FPGAs

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DBFS: Dynamic Bitwidth-Frequency Scaling for Efficient Software-defined SIMD

Highly Parallel RTL Simulation

Swift : a modern highly parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

EdgeAI-Aware Design of In-Memory Computing Architectures

Evaluating, Exploiting, and Hiding Power Side-Channel Leakage of Remote FPGAs

A Visionary Look at the Security of Reconfigurable Cloud Computing

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

Practical Implementations of Remote Power Side-Channel and Fault-Injection Attacks on Multitenant FPGAs

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

IIBLAST: Speeding Up Commercial FPGA Routing by Decoupling and Mitigating the Intra-CLB Bottleneck

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

Automating the Design of Programmable Interconnect for Reconfigurable Architectures

Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference

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

Challenging the Assumptions: Rethinking Privacy, Bias, and Security in Machine Learning

On Energy Control of Modular Multilevel Converters

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

Protection unit for wide bandgap power switching device and method for operating the wide bandgap power switching device

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