Publications associées à Auto-Partitioning Heterogeneous Task-Parallel Programs with StreamBlocks

Publications associées (7)

Dalton: Learned Partitioning for Distributed Data Streams

Anastasia Ailamaki, Ioannis Mytilinis, Eleni Zapridou

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

Error Resilient In-Memory Computing Architecture for CNN Inference on the Edge

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Flavio Ponzina, Marco Antonio Rios

The growing popularity of edge computing has fostered the development of diverse solutions to support Artificial Intelligence (AI) in energy-constrained devices. Nonetheless, comparatively few efforts have focused on the resiliency exhibited by AI workload ...

2022

Generating hardware and software for RISC-V cores generated with Rocket Chip generator

Endri Bezati

This paper presents the hardware/software generation backend of a code generation framework. The backend aims at synthesizing complete systems based on RISC-V cores with accelerators from a single-language description. The framework takes the dataflow desc ...

IEEE2021

Scaling Out Bioinformatics in the Data Center

Sam David Whitlock

Whole Genome Sequencing is a process in the field of bioinformatics that transforms biological samples of DNA into an electronic dataset of genetic bases. The process consists of two sequential components. First, the laboratory process of sequencing transf ...

EPFL2019

Parallelizing Query Optimization on Shared-Nothing Architectures

Christoph Koch, Immanuel Trummer

Data processing systems offer an ever increasing degree of parallelism on the levels of cores, CPUs, and processing nodes. Query optimization must exploit high degrees of parallelism in order not to gradually become the bottleneck of query evaluation. We s ...

Assoc Computing Machinery2016

Automated Design Flow for Multi-Functional Dataflow-Based Platforms

Marco Mattavelli, Endri Bezati, Simone Casale Brunet

The implementation of processing platforms supporting multiple applications by runtime reconfigurations on dedicated hardware modules requires the solution of different problems. These problems are notably not-trivial since both platform and application co ...

Springer Verlag2015

Dataflow Program Analysis and Refactoring Techniques for Design Space Exploration: MPEG-4 AVC/H.264 Decoder Implementation Case Study

Marco Mattavelli, Simone Casale Brunet, Claudio Paolo Alberti, Ab Al Hadi Bin Ab Rahman

This paper presents a methodology to perform design space exploration of complex signal processing systems implemented using the CAL dataflow language. In the course of space exploration, critical path in dataflow programs is first presented, and then anal ...

IEEE2013