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In the construction of exascale computing systems energy efficiency and power consumption are two of the major challenges. Low-power high performance embedded systems are of increasing interest as building blocks for large scale high-…

硬件体系结构 · 计算机科学 2014-11-03 Anish Varghese , Bob Edwards , Gaurav Mitra , Alistair P. Rendell

The Epiphany is a many-core, low power, low on-chip memory architecture and one can very cheaply gain access to a number of parallel cores which is beneficial for HPC education and prototyping. The very low power nature of these…

分布式、并行与集群计算 · 计算机科学 2020-10-29 Nick Brown

The Adapteva Epiphany many-core architecture comprises a 2D tiled mesh Network-on-Chip (NoC) of low-power RISC cores with minimal uncore functionality. It offers high computational energy efficiency for both integer and floating point…

分布式、并行与集群计算 · 计算机科学 2015-06-18 James A. Ross , David A. Richie , Song J. Park , Dale R. Shires

In this paper we use the Adapteva Epiphany manycore chip to demonstrate how the throughput and the latency of a baseband signal processing chain, typically found in LTE or WiFi, can be optimized by a combination of task- and data…

分布式、并行与集群计算 · 计算机科学 2015-12-18 Peter Brauer , Martin Lundqvist , Aare Mällo

The energy-efficient Adapteva Epiphany architecture exhibits massive many-core scalability in a physically compact 2D array of RISC cores with a fast network-on-chip (NoC). The architecture presents many features and constraints which…

分布式、并行与集群计算 · 计算机科学 2017-01-18 David A. Richie , James A. Ross

The Parallella is a hybrid computing platform that came into existence as the result of a Kickstarter project by Adapteva. It is composed of the high performance, energy-efficient, manycore architecture, Epiphany chip (used as co-processor)…

分布式、并行与集群计算 · 计算机科学 2016-11-17 Miguel Tasende

There is interest in exploring hybrid OpenSHMEM + X programming models to extend the applicability of the OpenSHMEM interface to more hardware architectures. We present a hybrid OpenCL + OpenSHMEM programming model for device-level…

分布式、并行与集群计算 · 计算机科学 2017-01-18 David Richie , James Ross

This paper reports the implementation and performance evaluation of the OpenSHMEM 1.3 specification for the Adapteva Epiphany architecture within the Parallella single-board computer. The Epiphany architecture exhibits massive many-core…

分布式、并行与集群计算 · 计算机科学 2017-01-18 James Ross , David Richie

The Adapteva Epiphany many-core architecture comprises a scalable 2D mesh Network-on-Chip (NoC) of low-power RISC cores with minimal uncore functionality. Whereas such a processor offers high computational energy efficiency and parallel…

分布式、并行与集群计算 · 计算机科学 2017-04-28 David Richie , James Ross , Jamie Infantolino

Micro-core architectures combine many low memory, low power computing cores together in a single package. These are attractive for use as accelerators but due to limited on-chip memory and multiple levels of memory hierarchy, the way in…

分布式、并行与集群计算 · 计算机科学 2020-10-06 Maurice Jamieson , Nick Brown

Today, many scientific and engineering areas require high performance computing to perform computationally intensive experiments. For example, many advances in transport phenomena, thermodynamics, material properties, computational…

分布式、并行与集群计算 · 计算机科学 2016-07-15 K. G. Kapanova , J. M. Sellier

In the field of High Performance Computing, communications among processes represent a typical bottleneck for massively parallel scientific applications. Object of this research is the development of a network interface card with specific…

分布式、并行与集群计算 · 计算机科学 2022-09-07 Roberto Ammendola

The growing capacity of integration allows to instantiate hundreds of soft-core processors in a single FPGA to create a reconfigurable multiprocessing system. Lately, FPGAs have been proven to give a higher energy efficiency than…

分布式、并行与集群计算 · 计算机科学 2016-05-03 David Castells-Rufas , Albert Saa-Garriga , Jordi Carrabina

In this paper, we propose LoopLynx, a scalable dataflow architecture for efficient LLM inference that optimizes FPGA usage through a hybrid spatial-temporal design. The design of LoopLynx incorporates a hybrid temporal-spatial architecture,…

硬件体系结构 · 计算机科学 2025-04-15 Jianing Zheng , Gang Chen

In this work, we propose a configurable many-core overlay for high-performance embedded computing. The size of internal memory, supported operations and number of ports can be configured independently for each core of the overlay. The…

硬件体系结构 · 计算机科学 2014-08-25 Mário Véstias , Horácio Neto

The processor accelerators are effective because they are working not (completely) on principles of stored program computers. They use some kind of parallelism, and it is rather hard to program them effectively: a parallel architecture by…

分布式、并行与集群计算 · 计算机科学 2016-08-26 János Végh

Heterogeneous many-cores are now an integral part of modern computing systems ranging from embedding systems to supercomputers. While heterogeneous many-core design offers the potential for energy-efficient high-performance, such potential…

分布式、并行与集群计算 · 计算机科学 2020-05-11 Jianbin Fang , Chun Huang , Tao Tang , Zheng Wang

With the appearance of the heterogeneous platform OpenPower,many-core accelerator devices have been coupled with Power host processors for the first time. Towards utilizing their full potential, it is worth investigating performance…

分布式、并行与集群计算 · 计算机科学 2016-11-07 Erik Zenker , René Widera , Axel Huebl , Guido Juckeland , Andreas Knüpfer , Wolfgang E. Nagel , Michael Bussmann

Large scale simulations are a key pillar of modern research and require ever-increasing computational resources. Different novel manycore architectures have emerged in recent years on the way towards the exascale era. Performance…

分布式、并行与集群计算 · 计算机科学 2020-07-17 Philipp Grete , Forrest W. Glines , Brian W. O'Shea

The vision of super computer at every desk can be realized by powerful and highly parallel CPUs or GPUs or APUs. Graphics processors once specialized for the graphics applications only, are now used for the highly computational intensive…

分布式、并行与集群计算 · 计算机科学 2012-04-16 Chittampally Vasanth Raja , Srinivas Balasubramanian , Prakash S Raghavendra
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