Modern computing has many foundational building blocks, including central processing units (CPUs), graphics processing units (GPUs) and data processing units (DPUs). However, what almost all modern ...
Abstract: In this paper, we propose a model-based workflow to generate parallel code on a multiple instruction stream, multiple data stream (MIMD) processor with vector accelerator (MIMDV) from a ...
ParaMonte has been developed while bearing the following design goals in mind: Full automation of Monte Carlo and Machine Learning simulations as much as possible to ensure user-friendliness of the ...
The financial institution is researching the possibilities of quantum computing and validating use cases for the coming quantum disruption. As CIO Chintan Mehta puts it, “Not engaging is not an option ...
Today, we’re excited to announce the release of SynapseML (previously MMLSpark), an open-source library that simplifies the creation of massively scalable machine learning (ML) pipelines. Building ...
This library provides data parallel C++ container classes with internal memory layout that is transformed to map efficiently to SIMD architectures. CSHIFT facilities are provided, similar to HPF and ...
Abstract: Composability is a key component to improve programmers' productivity in writing fast market-expanding applications such as parallel machine learning algorithms and big data analytics. These ...
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