Search results for "Hard"
showing 10 items of 2294 documents
Online Scheduling of Task Graphs on Hybrid Platforms
2018
Modern computing platforms commonly include accelerators. We target the problem of scheduling applications modeled as task graphs on hybrid platforms made of two types of resources, such as CPUs and GPUs. We consider that task graphs are uncovered dynamically, and that the scheduler has information only on the available tasks, i.e., tasks whose predecessors have all been completed. Each task can be processed by either a CPU or a GPU, and the corresponding processing times are known. Our study extends a previous \(4\sqrt{m/k}\)-competitive online algorithm [2], where m is the number of CPUs and k the number of GPUs (\(m\ge k\)). We prove that no online algorithm can have a competitive ratio …
Hybrid P2P schemes for remote terrain interactive visualization systems
2013
Over the last few years, there has been a lot of development of interactive terrain visualization applications using remote databases. One of the main problems that these applications must face is scalability. These applications usually use a client-server model that cannot support a large number of concurrent requests without using a considerable number of servers. In this paper, we present a full comparative study of new hybrid P2P schemes for terrain interactive visualization systems. The performance evaluation results show that the best strategy consists of avoiding the periodical reporting among peer nodes about the current information contained in each node, while using some servers a…
Multi-application Based Network-on-Chip Design for Mesh-of-Tree Topology Using Global Mapping and Reconfigurable Architecture
2019
This paper outlines a multi-application mapping for Mesh-of-Tree (MoT) topology based Network-on-Chip (NoC) design using reconfigurable architecture. A two phase Particle Swarm Optimization (PSO) has been proposed for reconfigurable architecture to minimize the communication cost. In first phase global mapping is done by combining multiple applications and in second phase, reconfiguration is achieved by switching the cores to near by routers using multiplexers. Experimentations have been carried out for several application benchmarks and synthetic applications generated using TGFF tool. The results show significant improvement in terms of communication cost after reconfiguration.
Fault-Tolerant Network-on-Chip Design for Mesh-of-Tree Topology Using Particle Swarm Optimization
2018
As the size of the chip is scaling down the density of Intellectual Property (IP) cores integrated on a chip has been increased rapidly. The communication between these IP cores on a chip is highly challenging. To overcome this issue, Network-on-Chip (NoC) has been proposed to provide an efficient and a scalable communication architecture. In the deep sub-micron level NoCs are prone to faults which can occur in any component of NoC. To build a reliable and robust systems, it is necessary to apply efficient fault-tolerant techniques. In this paper, we present a flexible spare core placement in Mesh-of-Tree (MoT) topology using Particle Swarm Optimization (PSO) by considering IP core failures…
Torus Topology based Fault-Tolerant Network-on-Chip Design with Flexible Spare Core Placement
2018
The increase in the density of the IP cores being fabricated on a chip poses on-chip communication challenges and heat dissipation. To overcome these issues, Network-onChip (NoC) based communication architecture is introduced. In the nanoscale era NoCs are prone to faults which results in performance degradation and un-reliability. Hence efficient fault-tolerant methods are required to make the system reliable in contrast to diverse component failures. This paper presents a flexible spare core placement in torus topology based faulttolerant NoC design. The communications related to the failed core is taken care by selecting the best position for a spare core in the torus network. By conside…
Wireless NoC for Inter-FPGA Communication: Theoretical Case for Future Datacenters
2020
Integration of FPGAs in datacenters might have different motivations from acceleration to energy efficiency, but the goal of better performance tops all. FPGAs are being utilized in a variety of ways today, tightly coupled with heterogenous computing resources, and as a standalone network of homogenous resources. Open source software stacks, propriety tool chain, and programming languages with advanced methodologies are hitting hard on the programmability wall of the FPGAs. The deployment of FPGAs in datacenters will neither be sustainable nor economical, without realizing the multi-tenancy in multiple FPGAs. Inter-FPGA communication among multiple FPGAs remained relatively less addressed p…
A segmentation algorithm for noisy images
2005
International audience; This paper presents a segmentation algorithm for gray-level images and addresses issues related to its performance on noisy images. It formulates an image segmentation problem as a partition of a weighted image neighborhood hypergraph. To overcome the computational difficulty of directly solving this problem, a multilevel hypergraph partitioning has been used. To evaluate the algorithm, we have studied how noise affects the performance of the algorithm. The alpha-stable noise is considered and its effects on the algorithm are studied. Key words : graph, hypergraph, neighborhood hypergraph, multilevel hypergraph partitioning, image segmentation and noise removal.
Rings for Privacy: an Architecture for Large Scale Privacy-Preserving Data Mining
2021
This article proposes a new architecture for privacy-preserving data mining based on Multi Party Computation (MPC) and secure sums. While traditional MPC approaches rely on a small number of aggregation peers replacing a centralized trusted entity, the current study puts forth a distributed solution that involves all data sources in the aggregation process, with the help of a single server for storing intermediate results. A large-scale scenario is examined and the possibility that data become inaccessible during the aggregation process is considered, a possibility that traditional schemes often neglect. Here, it is explicitly examined, as it might be provoked by intermittent network connec…
On the Use of a GPU-Accelerated Mobile Device Processor for Sound Source Localization
2017
Abstract The growing interest to incorporate new features into mobile devices has increased the number of signal processing applications running over processors designed for mobile computing. A challenging signal processing field is acoustic source localization, which is attractive for applications such as automatic camera steering systems, human-machine interfaces, video gaming or audio surveillance. In this context, the emergence of systems-on-chip (SoC) that contain a small graphics accelerator (or GPU), contributes a notable increment of the computational capacity while partially retaining the appealing low-power consumption of embedded systems. This is the case, for example, of the Sam…
FeatherCNN: Fast Inference Computation with TensorGEMM on ARM Architectures
2020
Deep Learning is ubiquitous in a wide field of applications ranging from research to industry. In comparison to time-consuming iterative training of convolutional neural networks (CNNs), inference is a relatively lightweight operation making it amenable to execution on mobile devices. Nevertheless, lower latency and higher computation efficiency are crucial to allow for complex models and prolonged battery life. Addressing the aforementioned challenges, we propose FeatherCNN – a fast inference library for ARM CPUs – targeting the performance ceiling of mobile devices. FeatherCNN employs three key techniques: 1) A highly efficient TensorGEMM (generalized matrix multiplication) routine is app…