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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…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-01-18 David A. Richie , James A. Ross

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…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-29 Nick Brown

In this paper we introduce Epiphany as a high-performance energy-efficient manycore architecture suitable for real-time embedded systems. This scalable architecture supports floating point operations in hardware and achieves 50 GFLOPS/W in…

Hardware Architecture · Computer Science 2014-12-18 Andreas Olofsson , Tomas Nordström , Zain Ul-Abdin

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…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-06-18 James A. Ross , David A. Richie , Song J. Park , Dale R. Shires

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…

Distributed, Parallel, and Cluster Computing · Computer Science 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…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-01-18 James Ross , David Richie

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). With fully divergent cores capable of MIMD execution, the physical…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-04-15 James A. Ross , David A. Richie

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…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-12-18 Peter Brauer , Martin Lundqvist , Aare Mällo

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…

Distributed, Parallel, and Cluster Computing · Computer Science 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…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-06 Maurice Jamieson , Nick Brown

With the advent of the Exascale capability allowing supercomputers to perform at least $10^{18}$ IEEE 754 Double Precision (64 bits) operations per second, many concerns have been raised regarding the energy consumption of high-performance…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-05-12 Tobias Fischbach , Emmanuel Kieffer , Pascal Bouvry

This paper describes the design of a 1024-core processor chip in 16nm FinFet technology. The chip ("Epiphany-V") contains an array of 1024 64-bit RISC processors, 64MB of on-chip SRAM, three 136-bit wide mesh Networks-On-Chip, and 1024…

Hardware Architecture · Computer Science 2016-10-07 Andreas Olofsson

Exascale systems are predicted to have approximately one billion cores, assuming Gigahertz cores. Limitations on affordable network topologies for distributed memory systems of such massive scale bring new challenges to the current parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-05-27 Huda Ibeid , Rio Yokota , David Keyes

Supercomputers become faster as hardware and software technologies continue to evolve. Current supercomputers are capable of 1015 floating point operations per second (FLOPS) that called Petascale system. The High Performance Computer (HPC)…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-09-27 Jalal Abdulbaqi

In the wake of the success of convolutional neural networks in image classification, object recognition, speech recognition, etc., the demand for deploying these compute-intensive ML models on embedded and mobile systems with tight power…

Computer Vision and Pattern Recognition · Computer Science 2019-11-12 Lukas Cavigelli , Georg Rutishauser , Luca Benini

New challenges in Astronomy and Astrophysics (AA) are urging the need for a large number of exceptionally computationally intensive simulations. "Exascale" (and beyond) computational facilities are mandatory to address the size of…

This work describes the challenges presented by porting parts ofthe Gysela code to the Intel Xeon Phi coprocessor, as well as techniques used for optimization, vectorization and tuning that can be applied to other applications. We evaluate…

Computational Physics · Physics 2015-08-04 G. Latu , M. Haefele , J. Bigot , V. Grandgirard , T. Cartier-Michaud , F. Rozar

FPGA accelerators on the NIC enable the offloading of expensive packet processing tasks from the CPU. However, FPGAs have limited resources that may need to be shared among diverse applications, and programming them is difficult. We present…

The success of the exascale supercomputer is largely debated to remain dependent on novel breakthroughs in technology that effectively reduce the power consumption and thermal dissipation requirements. In this work, we consider the…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-10-10 Sergio Rivas-Gomez , Antonio J. Peña , David Moloney , Erwin Laure , Stefano Markidis

The applications being developed within the U.S. Exascale Computing Project (ECP) to run on imminent Exascale computers will generate scientific results with unprecedented fidelity and record turn-around time. Many of these codes are based…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-08-04 Lipeng Wan , Axel Huebl , Junmin Gu , Franz Poeschel , Ana Gainaru , Ruonan Wang , Jieyang Chen , Xin Liang , Dmitry Ganyushin , Todd Munson , Ian Foster , Jean-Luc Vay , Norbert Podhorszki , Kesheng Wu , Scott Klasky
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