754 research outputs found
Natchez Trace Parkway, Tupelo Visitor Center
https://egrove.olemiss.edu/ms_pcards/1321/thumbnail.jp
Natchez Trace Parkway, Visitor Center
https://egrove.olemiss.edu/ms_pcards/1322/thumbnail.jp
Golfing On The Gulf
https://egrove.olemiss.edu/ms_pcards/1071/thumbnail.jp
Mississippi Gulf Coast, Year-A-Round Vacationland Postcard
This color double length postcard of the Mississippi Gulf Coast shows points of interest, principal highways, and a bird’s-eye view of the best vacationland in America. The front of the card appears as a map with various points of interest illustrations and the title Mississippi Gulf Coast Year-A-Round Vacationland in the lower right corner. The back of the card features the caption The Mississippi Gulf Coast...showing points of interest, principal highways, and a birdeye view of the best vacationland in America. as well as publisher and printer information. Three lines for writing are on the right half of the card and indication for postage stamp placement is in the upper right corner.https://scholarsjunction.msstate.edu/mss-lampton-images-ms-coast/1520/thumbnail.jp
Brandon, Mississippi, Confederate Memorial
https://egrove.olemiss.edu/ms_pcards/1055/thumbnail.jp
Along The Beach, Mississippi Gulf Coast
https://egrove.olemiss.edu/ms_pcards/1067/thumbnail.jp
Low precision matrix multiplication for efficient deep learning in NVIDIA Carmel processors
[EN] We introduce a high performance, multi-threaded realization of the gemm kernel for the ARMv8.2 architecture that operates with 16-bit (half precision)/queryKindly check and confirm whether the corresponding author is correctly identified. floating point operands. Our code is especially designed for efficient machine learning inference (and to a certain extent, also training) with deep neural networks. The results on the NVIDIA Carmel multicore processor, which implements the ARMv8.2 architecture, show considerable performance gains for the gemm kernel, close to the theoretical peak acceleration that could be expected when moving from 32-bit arithmetic/data to 16-bit. Combined with the type of convolution operator arising in convolutional neural networks, the speed-ups are more modest though still relevant.This work was supported by projects TIN2017-82972-R and RTI2018-093684-B-I00 from the Ministerio de Ciencia, Innovacion y Universidades, project S2018/TCS-4423 of the Comunidad de Madrid, project PR65/19-22445 of the UCM, and project Prometeo/2019/109 of the Generalitat Valenciana.San Juan-Sebastian, P.; RodrĂguez-Sánchez, R.; Igual, FD.; Alonso-Jordá, P.; Quintana-OrtĂ, ES. (2021). Low precision matrix multiplication for efficient deep learning in NVIDIA Carmel processors. The Journal of Supercomputing. 77(10):11257-11269. https://doi.org/10.1007/s11227-021-03636-41125711269771
Twelve year analysis of aerobic-only blood cultures for routine detection of bacteraemia
Sampling practices determine the accuracy of blood culture in diagnosing bloodstream infection. The main acute hospital in this study introduced aerobic-only routine blood cultures aiming to increase the volume and number of aerobic samples. At the smaller acute site, aerobic–anaerobic pairs were sent routinely. Culture yield and sampling practices were compared at these two sites and it was found that anaerobic cultures increased the yield of pathogens including facultative anaerobes. Volume cultured and number of samples sent fell short of national recommendations. The aerobic-only policy did not result in more blood being cultured. Based on these findings, the main acute hospital is reintroducing aerobic–anaerobic pairs for routine culture
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