@inproceedings{d68e73f31c534a27b3f324563e0b19d2,
title = "GPunet: Networking abstractions for GPU programs",
abstract = "Despite the popularity of GPUs in high-performance and scientific computing, and despite increasingly general-purpose hardware capabilities, the use of GPUs in network servers or distributed systems poses significant challenges. GPUnet is a native GPU networking layer that provides a socket abstraction and high-level networking APIs for GPU programs. We use GPUnet to streamline the development of high-performance, distributed applications like in-GPU-memory MapReduce and a new class of low-latency, high-throughput GPU-native network services such as a face verification server.",
author = "Sangman Kim and Seonggu Huh and Yige Hu and Xinya Zhang and Emmett Witchel and Amir Wated and Mark Silberstein",
note = "Publisher Copyright: {\textcopyright} 2014 by The USENIX Association. All Rights Reserved.; 11th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2014 ; Conference date: 06-10-2014 Through 08-10-2014",
year = "2014",
language = "الإنجليزيّة",
series = "Proceedings of the 11th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2014",
pages = "201--216",
booktitle = "Proceedings of the 11th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2014",
}