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Dynamic SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

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

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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 ...

SPRINGER2023

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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 ...

2023

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 ...

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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 ...

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Writing and optimizing application software for heterogeneous platforms including GPU units is a very difficult task that requires designer efforts and resources to consider several key elements to obtain good performance. Dataflow programming has shown to ...

2022

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Recent GPU architectures make available numbers of parallel processing units that exceed by orders of magnitude the ones offered by CPU architectures. Whereas programs written using dataflow programming languages are well suited for programming heterogeneo ...

IEEE2022

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The performance of programs executed on heterogeneous parallel platforms largely depends on the design choices regarding how to partition the processing on the various different processing units. In other words, it depends on the assumptions and parameters ...

MDPI2022

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The performance of programs written in languages following the dataflow model of computation (MoC) largely depends on the configuration (partitioning, mapping, scheduling, buffer dimensioning) chosen during the synthesis stages. Furthermore, this programmi ...

2022