Publications by Simone Casale Brunet

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

The impact of NFT profile pictures within social network communities

Marco Mattavelli, Simone Casale Brunet

This paper presents an analysis of the role of social media, specifically Twitter, in the context of non-fungible tokens, better known as NFTs. Such emerging technology framing the creation and exchange of digital object, started years ago with early proje ...

ACM2022

MPEG-G Reference-Based Compression of Unaligned Reads Through Ultra-Fast Alignments

Marco Mattavelli, Simone Casale Brunet, Ünsal Öztürk

IEEE2022

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

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

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Developing and fine-tuning software programs for heterogeneous hardware such as CPU/GPU processing platforms comprise a highly complex endeavor that demands considerable time and effort of software engineers and requires evaluating various fundamental comp ...

MDPI2022

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

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

Networks of Ethereum Non-Fungible Tokens: A graph-based analysis of the ERC-721 ecosystem

Marco Mattavelli, Simone Casale Brunet

Non-fungible tokens (NFTs) as a decentralized proof of ownership represent one of the main reasons why Ethereum is a disruptive technology. This paper presents the first systematic study of the interactions occurring in a number of NFT ecosystems. We illus ...

IEEE2021

Methodologies for Synthesizing and Analyzing Dynamic Dataflow Programs in Heterogeneous Systems for Edge Computing

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

The possibility of using the increasing computing power available in cloud infrastructures requires the development of new approaches for application software development and optimization. Emerging edge computing paradigms offer the possibility of reducing ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Pipeline Synthesis and Optimization from Branched Feedback Dataflow Programs

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

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

An Heterogeneous Compiler Of Dataflow Programs For Zynq Platforms

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

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

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

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

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

Shared-variable Synchronization Approaches for Dynamic Data Flow Programs

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

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

Efficient Dynamic Optimisation Heuristics for Dataflow Pipelines

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

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

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

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

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

High level synthesis of Smith-Waterman dataflow implementations

Marco Mattavelli, Endri Bezati, Simone Casale Brunet

The paper presents the results of design explorations for the implementation of the Smith-Waterman (S-W) algorithm executing DNA and protein sequences alignment. Both design explorations studies and the corresponding FPGA implementations are obtained by wr ...

2017

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

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

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

Design space exploration of dataflow-based Smith-Waterman FPGA implementations

Marco Mattavelli, Endri Bezati, Simone Casale Brunet

2017