◾ Circuit Emulation for Big Data Transfers in Clouds marat Zhanikeev

2015 ◽  
pp. 381-415
Keyword(s):  
Big Data ◽  
Big Data ◽  
2016 ◽  
pp. 43-95
Author(s):  
Se-young Yu ◽  
Nevil Brownlee ◽  
Aniket Mahanti

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Hiroyuki Takizawa ◽  
Shoichi Hirasawa ◽  
Makoto Sugawara ◽  
Isaac Gelado ◽  
Hiroaki Kobayashi ◽  
...  

In standard OpenCL programming, hosts are supposed to control their compute devices. Since compute devices are dedicated to kernel computation, only hosts can execute several kinds of data transfers such as internode communication and file access. These data transfers require one host to simultaneously play two or more roles due to the need for collaboration between the host and devices. The codes for such data transfers are likely to be system-specific, resulting in low portability. This paper proposes an OpenCL extension that incorporates such data transfers into the OpenCL event management mechanism. Unlike the current OpenCL standard, the main thread running on the host is not blocked to serialize dependent operations. Hence, an application can easily use the opportunities to overlap parallel activities of hosts and compute devices. In addition, the implementation details of data transfers are hidden behind the extension, and application programmers can use the optimized data transfers without any tricky programming techniques. The evaluation results show that the proposed extension can use the optimized data transfer implementation and thereby increase the sustained data transfer performance by about 18% for a real application accessing a big data file.


Author(s):  
Sergio Rivera ◽  
Jacob Chappell ◽  
Mami Hayashida ◽  
Andrew Groenewold ◽  
Peter Oostema ◽  
...  

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Taeuk Kim ◽  
Awais Khan ◽  
Youngjae Kim ◽  
Preethika Kasu ◽  
Scott Atchley

The evergrowing trend of big data has led scientists to share and transfer the simulation and analytical data across the geodistributed research and computing facilities. However, the existing data transfer frameworks used for data sharing lack the capability to adopt the attributes of the underlying parallel file systems (PFS). LADS (Layout-Aware Data Scheduling) is an end-to-end data transfer tool optimized for terabit network using a layout-aware data scheduling via PFS. However, it does not consider the NUMA (Nonuniform Memory Access) architecture. In this paper, we propose a NUMA-aware thread and resource scheduling for optimized data transfer in terabit network. First, we propose distributed RMA buffers to reduce memory controller contention in CPU sockets and then schedule the threads based on CPU socket and NUMA nodes inside CPU socket to reduce memory access latency. We design and implement the proposed resource and thread scheduling in the existing LADS framework. Experimental results showed from 21.7% to 44% improvement with memory-level optimizations in the LADS framework as compared to the baseline without any optimization.


2014 ◽  
pp. 316-323
Author(s):  
Tevaganthan Veluppillai ◽  
Brandon Ortiz ◽  
Robert E. Hiromoto

Several well-known data transfer protocols are presented in a comparative study to address the issue of big data transfer for tablet-class machines. The data transfer protocols include standard Java and C++, and block-data transfers protocols that use both the Java New IO (NIO) and the Zerocopy libraries, and a block-data C++ transfer protocol. Several experiments are described and results compared against the standard Java IO and C++ (stream-based file transport protocols). The motivation for this study is the development of a client/server big data file transport protocol for tablet-class client machines that rely on the Java Remote Method Invocation (RMI) package for distributed computing.


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