Výsledky vyhledávání - "Jeff A. Stuart"

Akademický článek

Avirulence effector discovery in a plant galling and plant parasitic arthropod, the Hessian fly (Mayetiola destructor).

Autor: Rajat Aggarwal, Subhashree Subramanyam, Chaoyang Zhao, Ming-Shun Chen, Marion O Harris, Jeff J Stuart

Publikováno v: PLoS ONE, Vol 9, Iss 6, p e100958 (2014)

Highly specialized obligate plant-parasites exist within several groups of arthropods (insects and mites). Many of these are important pests, but the molecular basis of their parasitism and its evolution are poorly understood. One hypothesis is that

Externí odkaz: https://doaj.org/article/fd0641efb2f0438fb9d2927ba8ee4112

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Out-of-core Data Management for Path Tracing on Hybrid Resources

Autor: John D. Owens, Kenneth I. Joy, Tony Bernardin, Brian Christopher Budge, Jeff A. Stuart, Shubhabrata Sengupta

Publikováno v: Budge, Brian C.; Bernardin, Tony; Stuart, Jeff A.; Sengupta, Shubhabrata; Joy, Ken; & Owens, John D.(2009). Out-of-core Data Management for Path Tracing on Hybrid Resources. UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/1750k9st

Author(s): Budge, Brian C.; Bernardin, Tony; Stuart, Jeff A.; Sengupta, Shubhabrata; Joy, Ken; Owens, John D. | Abstract: We present a software system that enables path-traced rendering of complex scenes. The system consists of two primary components

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03126a647ff0a949112c85a3622384ad
https://doi.org/10.1111/j.1467-8659.2009.01378.x

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A mitochondrial uncoupling artifact can be caused by expression of uncoupling protein 1 in yeast

Autor: Jeff A. STUART, James A. HARPER, Kevin M. BRINDLE, Mika B. JEKABSONS, Martin D. BRAND

Publikováno v: Biochemical Journal. 356:779-789

Uncoupling protein 1 (UCP1) from mouse was expressed in yeast and the specific (GDP-inhibitable) and artifactual (GDP-insensitive) effects on mitochondrial uncoupling were assessed. UCP1 provides a GDP-inhibitable model system to help interpret the u

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::808ca6daf8a54165c822af3f3e5a8551
https://doi.org/10.1042/bj3560779

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A Study of Persistent Threads Style GPU Programming for GPGPU Workloads

Autor: Kshitij Gupta, John D. Owens, Jeff A. Stuart

Publikováno v: Gupta, Kshitij; Stuart, Jeff A.; & Owens, John D.(2012). A Study of Persistent Threads Style GPU Programming for GPGPU Workloads. UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/3j76d3td

In this paper, we characterize and analyze an increasingly popular style of programming for the GPU called Persistent Threads (PT). We present a concise formal definition for this programming style, and discuss the difference between the traditional

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a8d9ac2d79ab7db5be6940ba3a452199
http://www.escholarship.org/uc/item/3j76d3td

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Multi-GPU MapReduce on GPU Clusters

Autor: Jeff A. Stuart, John D. Owens

Publikováno v: IPDPS
Stuart, Jeff A.; & Owens, John D.(2011). Multi-GPU MapReduce on GPU Clusters. UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/5rw127tw

We present GPMR, our stand-alone MapReduce library that leverages the power of GPU clusters for large-scale computing. To better utilize the GPU, we modify MapReduce by combining large amounts of map and reduce items into chunks and using partial red

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc5fd69ae8886ee1ec1eabdb4c1b44dd
https://doi.org/10.1109/ipdps.2011.102

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Extending MPI to Accelerators

Autor: Jeff A. Stuart, Pavan Balaji, John D. Owens

Publikováno v: Stuart, Jeff A.; Balaji, Pavan; & Owens, John D.(2011). Extending MPI to Accelerators. PACT 2011 Workshop Series: Architectures and Systems for Big Data. doi: 10.1145/2377978.2377981. UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/6xz3v4f9

Current trends in computing and system architecture point towards a need for accelerators such as GPUs to have inherent communication capabilities. We review previous and current software libraries that provide pseudo-communication abilities through

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::082d314685352359a12810657bcdc59b
http://www.escholarship.org/uc/item/6xz3v4f9

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GPU-to-CPU Callbacks

Autor: Michael Brian Cox, Jeff A. Stuart, John D. Owens

Publikováno v: Euro-Par 2010 Parallel Processing Workshops ISBN: 9783642218774
Euro-Par Workshops

We present GPU-to-CPU callbacks, a new mechanism and abstraction for GPUs that offers them more independence in a heterogeneous computing environment. Specifically, we provide a method for GPUs to issue callback requests to the CPU. These requests se

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0089c90bcd813dce4460baaa5ee6bfe3
https://doi.org/10.1007/978-3-642-21878-1_45

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Multi-GPU volume rendering using MapReduce

Autor: John D. Owens, Jeff A. Stuart, Kwan-Liu Ma, Cheng-Kai Chen

Publikováno v: HPDC
Stuart, Jeff A.; Chen, Cheng-Kai; Ma, Kwan-Liu; & Owens, John D.(2010). Multi-GPU Volume Rendering using MapReduce. 1st International Workshop on MapReduce and its Applications. doi: 10.1145/1851476.1851597. UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/65c2x71h

In this paper we present a multi-GPU parallel volume rendering implemention built using the MapReduce programming model. We give implementation details of the library, including specific optimizations made for our rendering and compositing design. We

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dee70eb51452d64becb9a83faa396ba6
https://doi.org/10.1145/1851476.1851597

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Message passing on data-parallel architectures

Autor: Jeff A. Stuart, John D. Owens

Publikováno v: IPDPS
Stuart, Jeff A.; & Owens, John D.(2009). Message Passing on Data-Parallel Architectures. UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/1vc4t6jg

This paper explores the challenges in implementing a message passing interface usable on systems with data-parallel processors. As a case study, we design and implement the ''DCGN'' API on NVIDIA GPUs that is similar to MPI and allows full access to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f6706efe0c5ad018c2092ddaa48a042
https://doi.org/10.1109/ipdps.2009.5161065

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