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Dynamic I/O Budget Reallocation For In Situ Wavelet Compression

Nicole J. Marsaglia, Shaomeng Li, Kristi Belcher, Matthew Larsen, Hank Childs
2019 Eurographics Symposium on Parallel Graphics and Visualization  
In situ wavelet compression is a potential solution for enabling post hoc visualization on supercomputers with slow I/O systems.  ...  While this in situ compression is typically accomplished by allocating an equal storage budget to each parallel process, we propose an adaptive approach.  ...  In terms of findings, this research shows that dynamically reallocating the I/O budget can lead to increased storage savings and more accurate output in some cases.  ... 
doi:10.2312/pgv.20191104 dblp:conf/egpgv/MarsagliaLBLC19 fatcat:7zs62pwzq5afvo7s7usu5xewi4

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1

Sue Denham, Panayiota Poirazi, Erik De Schutter, Karl Friston, Ho Ka Chan, Thomas Nowotny, Dongqi Han, Sungho Hong, Sophie Rosay, Tanja Wernle, Alessandro Treves, Sarah Goethals (+90 others)
2017 BMC Neuroscience  
This suggests a novel direction for compressive sensing theory and sampling methodology in engineered devices.  ...  Utilizing the sparsity of natural scenes, we derive a compressive-sensing based theoretical framework for network input reconstructions based on neuronal firing rate dynamics [1, 2].  ...  A change in the slope or gain of the I-O curve in the presence of different cellular and synaptic mechanisms, such as synaptic noise, shunting inhibition or synaptic plasticity is an indicator of ongoing  ... 
doi:10.1186/s12868-017-0370-3 fatcat:qq2cmqlotbg7vpqlqmmcql4u5i

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3

Adam J. H. Newton, Alexandra H. Seidenstein, Robert A. McDougal, Alberto Pérez-Cervera, Gemma Huguet, Tere M-Seara, Caroline Haimerl, David Angulo-Garcia, Alessandro Torcini, Rosa Cossart, Arnaud Malvache, Kaoutar Skiker (+526 others)
2017 BMC Neuroscience  
This suggests a novel direction for compressive sensing theory and sampling methodology in engineered devices.  ...  Utilizing the sparsity of natural scenes, we derive a compressive-sensing based theoretical framework for network input reconstructions based on neuronal firing rate dynamics [1, 2].  ...  A change in the slope or gain of the I-O curve in the presence of different cellular and synaptic mechanisms, such as synaptic noise, shunting inhibition or synaptic plasticity is an indicator of ongoing  ... 
doi:10.1186/s12868-017-0372-1 fatcat:q5x3vgivujgshmtthc6ki4fcfu

Accuracy- and resource-aware framework for resource-constrained mobile computing

Parul Pandey
2019
, CPU cycles,memory, and I/O data rate).  ...  Mobile computing is one of the largest untapped reservoirs in today's pervasive computing world as it has the potential to enable a variety of in-situ, real-time applications.  ...  , memory, and I/O data rate).  ... 
doi:10.7282/t3-sxb0-7n70 fatcat:7ktdkal3mngf5juhjoiid4wtqq

Issue 4-May 2012-Mastering Complexity: an Overview Mastering Complexity Mastering Complexity: an Overview

Claude Barrouil
unpublished
Otherwise, simulation budget, dimension of the problem or density models also play an important role in the selection of the most efficient and suitable methods.  ...  Conclusion In this article, we have presented a large spectrum of methods for evaluating performances of complex systems that could significantly improve the results obtained with classical algorithms.  ...  And finally, dedicated I/O interfaces are replaced by common I/O interfaces (and the associated wiring). Globally, IMA results in a reduction in the required physical resources.  ... 
fatcat:ctmfmyn6gfclnecdecgv27uh74

Segmentation and Deformable Modelling Techniques for a Virtual Reality Surgical Simulator in Hepatic Oncology

Ying Chi, Peter Cashman, Richard Kitney, Lee Family Scholarship
2009
There is a need for a computer-assisted surgical planning and simulation system which can accurately and efficiently simulate the liver, vessels and tumours in actual patients.  ...  This project was implemented in conjunction w [...]  ...  − ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ − + − − = ∂ ∂ N K N A M I A M I M M t C o o i i o i γ ) ( , (5.1) where γ is a weighting term, K is the curvature.  ... 
doi:10.25560/4350 fatcat:bfzg7gztg5eb5mxqsyvxccbrnq