1,668 research outputs found
Pipelining the Fast Multipole Method over a Runtime System
Fast Multipole Methods (FMM) are a fundamental operation for the simulation
of many physical problems. The high performance design of such methods usually
requires to carefully tune the algorithm for both the targeted physics and the
hardware. In this paper, we propose a new approach that achieves high
performance across architectures. Our method consists of expressing the FMM
algorithm as a task flow and employing a state-of-the-art runtime system,
StarPU, in order to process the tasks on the different processing units. We
carefully design the task flow, the mathematical operators, their Central
Processing Unit (CPU) and Graphics Processing Unit (GPU) implementations, as
well as scheduling schemes. We compute potentials and forces of 200 million
particles in 48.7 seconds on a homogeneous 160 cores SGI Altix UV 100 and of 38
million particles in 13.34 seconds on a heterogeneous 12 cores Intel Nehalem
processor enhanced with 3 Nvidia M2090 Fermi GPUs.Comment: No. RR-7981 (2012
CoAP Infrastructure for IoT
The Internet of Things (IoT) can be seen as a large-scale network of billions of smart devices. Often IoT
devices exchange data in small but numerous messages, which requires IoT services to be more scalable and
reliable than ever. Traditional protocols that are known in the Web world does not fit well in the constrained
environment that these devices operate in. Therefore many lightweight protocols specialized for the IoT have
been studied, among which the Constrained Application Protocol (CoAP) stands out for its well-known REST
paradigm and easy integration with existing Web. On the other hand, new paradigms such as Fog Computing
emerges, attempting to avoid the centralized bottleneck in IoT services by moving computations to the edge
of the network. Since a node of the Fog essentially belongs to relatively constrained environment, CoAP fits
in well. Among the many attempts of building scalable and reliable systems, Erlang as a typical concurrency-oriented programming (COP) language has been battle tested in the telecom industry, which has similar requirements
as the IoT. In order to explore the possibility of applying Erlang and COP in general to the IoT, this thesis
presents an Erlang based CoAP server/client prototype ecoap with a flexible concurrency model that can
scale up to an unconstrained environment like the Cloud and scale down to a constrained environment like
an embedded platform. The flexibility of the presented server renders the same architecture applicable from
Fog to Cloud. To evaluate its performance, the proposed server is compared with the mainstream CoAP
implementation on an Amazon Web Service (AWS) Cloud instance and a Raspberry Pi 3, representing the
unconstrained and constrained environment respectively. The ecoap server achieves comparable throughput,
lower latency, and in general scales better than the other implementation in the Cloud and on the Raspberry
Pi. The thesis yields positive results and demonstrates the value of the philosophy of Erlang in the IoT space
5G Cellular: Key Enabling Technologies and Research Challenges
The evolving fifth generation (5G) cellular wireless networks are envisioned
to provide higher data rates, enhanced end-user quality-of-experience (QoE),
reduced end-to-end latency, and lower energy consumption. This article presents
several emerging technologies, which will enable and define the 5G mobile
communications standards. The major research problems, which these new
technologies breed, as well as the measurement and test challenges for 5G
systems are also highlighted.Comment: IEEE Instrumentation and Measurement Magazine, to appear in the June
2015 issue. arXiv admin note: text overlap with arXiv:1406.6470 by other
author
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