A simulator for adaptive parallel applications

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Zoning reform is a crucial tool for cities to adapt to contemporary challenges. However, its implementation remains challenging. Property owners, with a vested interest in the value of their neighborhoods, are sensitive to local developments and the potent ...

Interactive mobile applications like web browsing and gaming are known to benefit significantly from low latency networking, as applications communicate with cloud servers and other users' devices. Emerging mobile channel standards have not met these needs ...

In this work, we provide important parameters to take into account when fabricating in-plane III-V photodetectors (PDs) integrated on silicon (Si) using template-assisted selective epitaxy (TASE). Their performance has previously been demonstrated, and her ...

We present a simulation method to estimate the dark count rate (DCR), photon detection probability (PDP), and dark current of InGaAs/InP single-photon avalanche diodes (SPADs) from 225K to 300K. All simulations are performed completely in TCAD and match we ...

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 ...

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 ...

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 ...

Characterizing the genetic structure of large cohorts has become increasingly important as genetic studies extend to massive, increasingly diverse biobanks. Popular methods decompose individual genomes into fractional cluster assignments with each cluster ...

Low-level light detection with high spatial and timing accuracy is a growing area of interest by virtue of applications such as light detection and ranging (LiDAR), biomedical imaging, time-resolved Raman spectroscopy, and quantum applications. Single-phot ...

With the advent of the Square Kilometre Array Observatory (SKAO), scientists will be able to directly observe the Epoch of Reionization by mapping the distribution of neutral hydrogen at different redshifts. While physically motivated results can be simula ...

This paper presents a novel simulation approach for generating synthetic households, addressing several literature gaps from the methodological viewpoint. The generation of hierarchical datasets such as complete households is challenging since it must guar ...

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

Deep learning (DL) has recently been proposed as a novel approach for 21cm foreground removal. Before applying DL to real observations, it is essential to assess its consistency with established methods, its performance across various simulation models, an ...

Computational chemistry techniques offer tremendous potential for accelerating the discovery of sustainable chemical processes and reactions. However, the environmental impacts of the substantial computing power required for these digital methods are often ...

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 ...

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 ...

To understand how daylight gives shape and life to architectural spaces, whether existing or imagined, requires quantifying its dynamism and energy. Maintaining these details presents a challenge to simulation and analysis methods that flatten data into di ...

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 ...

Control design for robotic systems is complex and often requires solving an optimization to follow a trajectory accurately. Online optimization approaches like Model Predictive Control (MPC) have been shown to achieve great tracking performance, but requir ...

K-means is one of the fundamental unsupervised data clustering and machine learning methods. It has been well studied over the years: parallelized, approximated, and optimized for different cases and applications. With increasingly higher parallelism leadi ...

A simulator for adaptive parallel applications

Chattez avec Graph Search

Spatial Modeling for Building Design Evaluation: from Visual Landscape Quality Assessment to Devaluation Risk Estimation

DChannel: Accelerating Mobile ApplicationsWith Parallel High-bandwidth and Low-latency Channels

Simulation and Fabrication of Monolithic III-V Photodetectors on Si: The Role of Growth Facets and Localization of Heterojunctions

Extended Temperature Modeling of InGaAs/InP SPADs

Overflow-free compute memories for edge AI acceleration

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

Benchmarking quantum computer simulation software packages: State vector simulators

Neural ADMIXTURE for rapid genomic clustering

Advanced Silicon and SWIR Single-Photon Avalanche Diodes: Design, Simulation, and Characterization

PINION: physics-informed neural network for accelerating radiative transfer simulations for cosmic reionization

Divide-and-conquer one-step simulator for the generation of synthetic households

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

The stability of deep learning for 21cm foreground removal across various sky models and frequency-dependent systematics

Balancing computational chemistry's potential with its environmental impact

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

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

Traversing Time Dependent Light Fields for Daylight Glare Evaluation

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

Training Efficient Controllers via Analytic Policy Gradient

Improving K-means Clustering Using Speculation