Search results for "Parallel"

Live demonstration: multiplexing AER asynchronous channels over LVDS Links with Flow-Control and Clock-Correction for Scalable Neuromorphic Systems

2017

Paper presented at the 2017 IEEE International Symposium on Circuits and Systems (ISCAS), held in Baltimore, MD, USA, on 28-31 May 2017.

The Sliced COO Format for Sparse Matrix-Vector Multiplication on CUDA-enabled GPUs

2012

Abstract Existing formats for Sparse Matrix-Vector Multiplication (SpMV) on the GPU are outperforming their corresponding implementations on multi-core CPUs. In this paper, we present a new format called Sliced COO (SCOO) and an effcient CUDA implementation to perform SpMV on the GPU. While previous work shows experiments on small to medium-sized sparse matrices, we perform evaluations on large sparse matrices. We compared SCOO performance to existing formats of the NVIDIA Cusp library. Our resutls on a Fermi GPU show that SCOO outperforms the COO and CSR format for all tested matrices and the HYB format for all tested unstructured matrices. Furthermore, comparison to a Sandy-Bridge CPU sho…

Improving LSM‐trie performance by parallel search

2020

A Methodology for the Analysis of Memory Response to Radiation through Bitmap Superposition and Slicing

2015

A methodology is proposed for the statistical analysis of memory radiation test data, with the aim of identifying trends in the single-even upset (SEU) distribution. The treated case study is a 65nm SRAM irradiated with neutrons, protons and heavy-ions.

Parallel implementation on DSPs of a face detection algorithm

2002

In order to localize the face in an image, our approach consists of approximating the face oval shape with an ellipse and to compute coordinates of the center of the ellipse. For this purpose, we explore a new version of the Hough transformation: the fuzzy generalized Hough transformation. To reduce the computation time, we present also a parallel implementation of the algorithm on 2 digital signal processors and we show that an acceleration of a factor of 1.62 has been obtained.

A new autonomous data transmission reduction method for wireless sensors networks

2018

International audience; The inherent limitation in energy resources and computational power for sensor nodes in a Wireless Sensor Network, poses the challenge of extending the lifetime of these networks. Since radio communication is the dominant energy consuming activity, most presented approaches focused on reducing the number of data transmitted to the central workstation. This can be achieved by deploying both on the workstation and the sensor node a synchronized prediction model capable of forecasting future values. Thus, enabling the sensor node to transmit only the values that surpasses a predefined error threshold. This mechanism offers a decrease in the cost of transmission energy f…

Efficient Hybrid Emergency Aware MAC Protocol for Wireless Body Sensor Networks

2018

International audience; In Body Sensor Networks (BSNs), two types of events should be addressed: periodic and emergency events. Traffic rate is usually low during periodic observation, and becomes very high upon emergency. One of the main and challenging requirements of BSNs is to design Medium Access Control (MAC) protocols that guarantee immediate and reliable transmission of data in emergency situations, while maintaining high energy efficiency in non-emergency conditions. In this paper, we propose a new emergency aware hybrid DTDMA/DS-CDMA protocol that can accommodate BSN traffic variations by addressing emergency and periodic traffic requirements. It takes advantage of the high delay …

The Stability-Plasticity Dilemma: Investigating the Continuum from Catastrophic Forgetting to Age-Limited Learning Effects

2013

The stability-plasticity dilemma is a well-know constraint for artificial and biological neural systems. The basic idea is that learning in a parallel and distributed system requires plasticity for the integration of new knowledge, but also stability in order to prevent the forgetting of previous knowledge. Too much plasticity will result in previously encoded data being constantly forgotten, whereas too much stability will impede the efficient coding of this data at the level of the synapses. However, for the most part, neural computation has addressed the problems related to excessive plasticity or excessive stability as two different fields in the literature.

A Parallel Approach to HRTF Approximation and Interpolation Based on a Parametric Filter Model

2017

[EN] Spatial audio-rendering techniques using head-related transfer functions (HRTFs) are currently used in many different contexts such as immersive teleconferencing systems, gaming, or 3-D audio reproduction. Since all these applications usually involve real-time constraints, efficient processing structures for HRTF modeling and interpolation are necessary for providing real-time binaural audio solutions. This letter presents a parametric parallel model that allows us to perform HRTF filtering and interpolation efficiently from an input HRTF dataset. The resulting model, which is an adaptation from a recently proposed modeling technique, not only reduces the size of HRTF datasets signific…

A Generic Approach to Scheduling and Checkpointing Workflows

2018

This work deals with scheduling and checkpointing strategies to execute scientific workflows on failure-prone large-scale platforms. To the best of our knowledge, this work is the first to target fail-stop errors for arbitrary workflows. Most previous work addresses soft errors, which corrupt the task being executed by a processor but do not cause the entire memory of that processor to be lost, contrarily to fail-stop errors. We revisit classical mapping heuristics such as HEFT and MinMin and complement them with several checkpointing strategies. The objective is to derive an efficient trade-off between checkpointing every task (CkptAll), which is an overkill when failures are rare events, …