Publications related to Dataflow

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

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

SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

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

Dalton: Learned Partitioning for Distributed Data Streams

Anastasia Ailamaki, Eleni Zapridou, Ioannis Mytilinis

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

Pipeline Synthesis and Optimization from Branched Feedback Dataflow Programs

Marco Mattavelli, Simone Casale Brunet, Endri Bezati, Anatoly Prihozhy

Large dataflow designs are a result of behavioral specification of modern complex digital systems and/or a result of unfolding and transforming looped and branched programs. Since deep-submicron silicon technology provides large amounts of available resour ...

SPRINGER2020

Composite Data Types in Dynamic Dataflow Languages as Copyless Memory Sharing Mechanism

Marco Mattavelli, Endri Bezati, Aurélien François Gilbert Bloch

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

An Heterogeneous Compiler Of Dataflow Programs For Zynq Platforms

Marco Mattavelli, Simone Casale Brunet, Romuald Mosqueron, Endri Bezati

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

Shared-variable Synchronization Approaches for Dynamic Data Flow Programs

Marco Mattavelli, Simone Casale Brunet, Endri Bezati, Apostolos Modas, Junaid Jameel Ahmad

This paper presents shared-variable synchronization approaches for dataflow programming. The mechanisms do not require any substantial model of computation (MoC) modification, and is portable across both for hardware (HW) and software (SW) low-level code s ...

IEEE2018

Execution Trace Graph of Dataflow Process Networks

Marco Mattavelli, Simone Casale Brunet

The paper introduces and specifies a formalism that provides complete representations of dataflow process network (DPN) program executions, by means of directed acyclic graphs. Such graphs, also known as execution trace graphs (ETG), are composed of nodes ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

High-Precision Performance Estimation for the Design Space Exploration of Dynamic Dataflow Programs

Marco Mattavelli, Malgorzata Maria Michalska, Simone Casale Brunet, Endri Bezati

The implementation and optimization of dynamic dataflow programs on multi/many-core platforms require solving a very difficult problem: how to partition and schedule the processing elements and dimension their interconnecting buffers according to given opt ...

2017

Efficient Dynamic Optimisation Heuristics for Dataflow Pipelines

Marco Mattavelli, Simone Casale Brunet, Endri Bezati, Anatoly Prihozhy

Large dataflow designs appear as a result of functional specification of modern complex digital systems and/ or a result of unfolding and behavioral transformation of looped and branched programs. Since deep-submicron silicon technology provides large amou ...

IEEE2018

Buffer dimensioning for throughput improvement of dynamic dataflow signal processing applications on multi-core platforms

Marco Mattavelli, Malgorzata Maria Michalska, Simone Casale Brunet, Endri Bezati

Executing a dataflow program on a parallel platform requires assigning to each buffer a given size so that correct program executions take place without introducing any deadlock. Furthermore, in the case of dynamic dataflow programs, specific buffer size a ...

2017

Performance estimation of program partitions on multi-core platforms, 2016 26th International Workshop on Power and Timing Modeling, Optimization and Simulation (PATMOS)

Marco Mattavelli, Simone Casale Brunet, Endri Bezati, Malgorzata Maria Michalska, Junaid Jameel Ahmad

The exploration of different design configurations of dynamic dataflow programs executed on many-core or multi-core platforms is, in general, a very difficult task. Determining a close-to-optimal partitioning, scheduling and buffer dimensioning configurati ...

2017

Systematic Design Space Exploration of Dynamic Dataflow Programs for Multi-core Platforms

Malgorzata Maria Michalska

The limitations of clock frequency and power dissipation of deep sub-micron CMOS technology have led to the development of massively parallel computing platforms. They consist of dozens or hundreds of processing units and offer a high degree of parallelism ...

EPFL2017

Near-optimal Deployment of Dataflow Applications on Many-core Platforms with Real-time Guarantees

Alena Simalatsar, Stefanos Skalistis

Safe and optimal deployment of data-streaming applications on many-core platforms requires the realistic estimation of task Worst-Case Execution Time (WCET). On the other hand, task WCET depends on the deployment solution, due to the varying number of inte ...

IEEE2017

Monotonicity Types for Distributed Dataflow

Heather Christine Klug

The Lasp programming language provides combinator functions such as Union and Intersection for combining set CRDTs. When designing a CRDT combinator, care must be taken to ensure that the combinator is monotone separately in each of its arguments, so that ...

2017