Full System Simulation of Many-Core Heterogeneous SoCs using GPU and QEMU Semihosting

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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 ...

The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

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 ...

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 invention relates to an Imaging sensor device in a stacked arrangement comprising: - a pixel array tier comprising a plurality of pixel segments each having a plurality of pixels for photon detection each providing a digital pixel output; - a processin ...

The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

Cloud computing environments increasingly provision field-programmable gate arrays (FPGAs) for their programmability and hardware-level parallelism. While FPGAs are typically used by one tenant at a time, multitenant schemes supporting spatial sharing of c ...

Rapid advances in quantum computing technology lead to an increasing need for software simulators that enable both algorithm design and the validation of results obtained from quantum hardware. This includes calculations that aim at probing regimes of quan ...

Computing servers have played a key role in developing and processing emerging compute-intensive applications in recent years. Consolidating multiple virtual machines (VMs) inside one server to run various applications introduces severe competence for limi ...

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 ...

2.5D Systems-on-Package (SoPs) are composed by several chiplets placed on an interposer. They are becoming increasingly popular as they enable easy integration of electronic components in the same package and high fabrication yields. Nevertheless, they int ...

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 ...

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

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 ...

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

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 ...

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 ...

Full System Simulation of Many-Core Heterogeneous SoCs using GPU and QEMU Semihosting

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Highly Parallel RTL Simulation

Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

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

EdgeAI-Aware Design of In-Memory Computing Architectures

Imaging sensor device using an array of single-photon avalanche diode photodetectors

Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

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

Benchmarking quantum computer simulation software packages: State vector simulators

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

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

REMOTE: Re-thinking Task Mapping on Wireless 2.5D Systems-on-Package for Hotspot Removal

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

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

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

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

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

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