A New Task Graph Model for Mapping Message Passing Applications

2007 ◽  
Vol 18 (12) ◽  
pp. 1740-1753 ◽  
Author(s):  
C. Roig ◽  
A. Ripoll ◽  
F. Guirado
Keyword(s):  
Message Passing ◽  
Graph Model ◽  
Task Graph

scholarly journals Exploiting a Parametrized Task Graph Model for the Parallelization of a Sparse Direct Multifrontal Solver

2017 ◽  
pp. 175-186 ◽  
Author(s):  
Emmanuel Agullo ◽  
George Bosilca ◽  
Alfredo Buttari ◽  
Abdou Guermouche ◽  
Florent Lopez
Keyword(s):  
Graph Model ◽  
Task Graph

scholarly journals DOF Decoupling Task Graph Model: Reducing the Complexity of Touch-Based Active Sensing

Robotics ◽  
2015 ◽  
Vol 4 (2) ◽  
pp. 141-168
Author(s):  
Niccoló Tosi ◽  
Olivier David ◽  
Herman Bruyninckx
Keyword(s):  
Graph Model ◽  
Task Graph ◽  
Active Sensing

PERFORMANCE ANALYSIS OF A JPEG ENCODER MAPPED ONTO A VIRTUAL MPSoC-NoC ARCHITECTURE USING TLM 2.0.1

2013 ◽  
Vol 22 (05) ◽  
pp. 1350036
Author(s):  
F. A. ESCOBAR-JUZGA ◽  
F. E. SEGURA-QUIJANO
Keyword(s):  
Message Passing ◽  
Programming Model ◽  
Task Graph ◽  
Modeling Tools ◽  
Networks On Chip ◽  
Hardware Description ◽  
On Chip ◽  
Network Speed ◽  
High Level ◽  
The Impact

Networks on Chip (NoCs) are commonly used to integrate complex embedded systems and multiprocessor platforms due to their scalability and versatility. Modeling tools used at the functional level use SystemC to perform hardware–software co-design and error correction concurrently, thus, reducing time to market. This work analyzes a JPEG encoding algorithm mapped onto a configurable M × N, mesh/torus, NoC platform described in SystemC with the transaction level modeling (TLM) standard; timing constraints for both, the router and network interface controller, are assigned according to a hardware description language (HDL) model written for this purpose. Processing nodes are also described as SystemC threads and their computation delays are assigned depending on the amount and cost of the operations they perform. The programming model employed is message passing. We start by describing and profiling the JPEG algorithm as a task graph; then, four partitioning proposals are mapped onto three NoCs of different size. Our analysis comprises changes in topology, virtual channel depth, routing algorithms, network speed and task-node assignments. Through several high-level simulations we evaluate the impact of each parameter and we show that, for the proposed model, most improvements come from the algorithm partitioning.

COMMUNICATION SCHEDULING WITH RE-ROUTING BASED ON STATIC AND HYBRID TECHNIQUES

2004 ◽  
Vol 13 (05) ◽  
pp. 1039-1064
Author(s):  
DAVID R. SURMA ◽  
EDWIN H.-M. SHA ◽  
NELSON PASSOS
Keyword(s):  
Message Passing ◽  
Dynamic Scheduling ◽  
A Priori ◽  
Dynamic Environment ◽  
Graph Model ◽  
Communication Overhead ◽  
Hybrid Technique ◽  
Static Scheduling ◽  
Hybrid Techniques ◽  
Tightly Coupled

In massively parallel systems, the performance gains are often significantly diminished by the inherent communication overhead. This overhead is caused by the required message passing resulting from the task allocation scheme. In this paper, techniques to reduce this communication overhead by both scheduling the communication and determining the routing that the messages should take within a tightly-coupled processor network are presented. Using the recently developed Collision Graph model, static scheduling algorithms are derived which work at compile-time to determine the ordering and routing of the individual message transmissions. Since a priori knowledge about the network traffic required by static scheduling may not be available or accurate, this work also considers dynamic scheduling. A novel hybrid technique is presented which operates in a dynamic environment yet uses known information obtained by analyzing the communication patterns. Experiments performed show significant improvement over baseline techniques.

scholarly journals Iterative Receiver Design for the Estimation of Gaussian Samples in Impulsive Noise

2020 ◽  
Author(s):  
Anoush Mirbadin ◽  
Armando Vannucci ◽  
Giulio Colavolpe ◽  
Riccardo Pecori ◽  
Luca Veltri
Keyword(s):  
Electromagnetic Interference ◽  
Message Passing ◽  
Impulsive Noise ◽  
Graph Model ◽  
Performance Comparison ◽  
Factor Graph ◽  
Limiting Factor ◽  
Receiver Design ◽  
Modern Approach ◽  
Channel Conditions

Impulsive noise is the main limiting factor for transmission over channels affected by electromagnetic interference. We study the estimation of (correlated) Gaussian signals in an impulsive noise scenarios. In this work, we analyze some of the existing as well as some novel estimation algorithms. Their performance is compared, for the first time, for different channel conditions, including the Markov-Middleton scenario, where the impulsive noise switches between different noise states. Following a modern approach in digital communications, the receiver design is based on a factor graph model and implements a message passing algorithm. The correlation among signal samples as well as among noise states brings about a loopy factor graph, where an iterative message passing scheme should be employed. As it is well known, approximate variational inference techniques are necessary in these cases. We propose and analyze different algorithms and provide a complete performance comparison among them, showing that both Expectation Propagation, Transparent Propagation, and the Parallel Iterative Schedule approaches reach a performance close to the optimal, at different channel conditions.

scholarly journals Iterative Receiver Design for the Estimation of Gaussian Samples in Impulsive Noise

2021 ◽  
Vol 11 (2) ◽  
pp. 557
Author(s):  
Anoush Mirbadin ◽  
Armando Vannucci ◽  
Giulio Colavolpe ◽  
Riccardo Pecori ◽  
Luca Veltri
Keyword(s):  
Electromagnetic Interference ◽  
Message Passing ◽  
Impulsive Noise ◽  
Graph Model ◽  
Performance Comparison ◽  
Factor Graph ◽  
Limiting Factor ◽  
Receiver Design ◽  
Modern Approach ◽  
Channel Conditions

Impulsive noise is the main limiting factor for transmission over channels affected by electromagnetic interference. We study the estimation of (correlated) Gaussian signals in an impulsive noise scenario. In this work, we analyze some of the existing, as well as some novel estimation algorithms. Their performance is compared, for the first time, for different channel conditions, including the Markov–Middleton scenario, where the impulsive noise switches between different noise states. Following a modern approach in digital communications, the receiver design is based on a factor graph model and implements a message passing algorithm. The correlation among signal samples, as well as among noise states brings about a loopy factor graph, where an iterative message passing scheme should be employed. As is well known, approximate variational inference techniques are necessary in these cases. We propose and analyze different algorithms and provide a complete performance comparison among them, showing that the expectation propagation, transparent propagation, and parallel iterative schedule approaches reach a performance close to optimal, at different channel conditions.

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