Concept

Dataflow

Related publications (76)

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Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

Aurélien François Gilbert Bloch

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

EPFL2023

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

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

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

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms by Dynamic Network Execution

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

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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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

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

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

Inter-actions parallel execution on GPU from high-level dataflow synthesis

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

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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To sustain the input rate of high-throughput streams, modern stream processing systems rely on parallel execution. However, skewed data yield imbalanced load assignments and create stragglers that hinder scalability. Deciding on a static partitioning for a ...

2022

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This paper presents new optimization approaches aiming at reducing the impact of memory accesses on the performance of dataflow programs. The approach is based on introducing a high level management of composite data types in dynamic dataflow programming l ...

2019

Shrink It or Shed It! Minimize the Use of LSQs in Dataflow Designs

Paolo Ienne, Andrea Guerrieri, Lana Josipovic, Atri Bhattacharyya

When applications have unpredictable memory accesses or irregular control flow, dataflow circuits overcome the limitations of statically scheduled high-level synthesis (HLS). If memory dependences cannot be determined at compile time, dataflow circuits rel ...

IEEE COMPUTER SOC2019

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In recent years, the number and variety of heterogeneous multiprocessor system-on-chip MPSoCs, such as for instance Zynq platforms, has sensibly increased. However, today all design flow solutions capable of programming the different components of such pla ...

IEEE2019