Here we present NeuroVault—a web based repository that allows researchers to store, share, visualize, and decode statistical maps of the human brain. NeuroVault is easy to use and employs modern web technologies to provide informative visualization of data without the need to install additional software. In addition, it leverages the power of the Neurosynth database to provide cognitive decoding of deposited maps. The data are exposed through a public REST API enabling other services and tools to take advantage of it. NeuroVault is a new resource for researchers interested in conducting meta- and coactivation analyses.
Compiler transformations can significantly improve data locality for many scientific programs. In this paper, we show iterative solvers for partial differential equations (PDEs) in three dimensions require new compiler optimizations not needed for 2D codes, since reuse along the third dimension cannot fit in cachefor larger problem sizes. Tiling is a program transformation compilers can apply to capture this reuse, but successful application of tiling requires selection of non-conflicting tiles and/or padding array dimensions to eliminate conflicts. We present new algorithms and cost models for selecting tiling shapes and array pads. We explain why tiling is rarely needed for 2D PDE solvers, but can be helpful for 3D stencil codes. Experimental results show tiling 3D codes can reduce miss rates and achieve performance improvements of 17-121% for key scientific kernels, including a 27% average improvement for the key computational loop nest in the SPEC/NAS benchmark MGRID.
Here we present NeuroVault -a web based repository that allows researchers to store, share, visualize, and decode statistical maps of the human brain. NeuroVault is easy to use and employs modern web technologies to provide informative visualization of data without the need to install additional software. In addition, it leverages the power of the Neurosynth database to provide cognitive decoding of deposited maps. The data are exposed through a public REST API enabling other services and tools to take advantage of it. NeuroVault is a new resource for researchers interested in conducting meta and coactivation analyses.
Abstract. Linear algebra codes contain data locality which can be exploited by tiling multiple loop nests. Several approaches to tiling have been suggested for avoiding conflict misses in low associativity caches. We propose a new technique based on intra-variable padding and compare its performance with existing techniques. Results show padding improves performance of matrix multiply by over 100% in some cases over a range of matrix sizes. Comparing the efficacy of different tiling algorithms, we discover rectangular tiles are slightly more efficient than square tiles. Overall, tiling improves performance from 0-250%. Copying tiles at run time proves to be quite effective.
NeuroVault.org is dedicated to storing outputs of analyses in
the form of statistical maps, parcellations and atlases, a unique strategy that
contrasts with most neuroimaging repositories that store raw acquisition data or
stereotaxic coordinates. Such maps are indispensable for performing
meta-analyses, validating novel methodology, and deciding on precise outlines
for regions of interest (ROIs). NeuroVault is open to maps derived from both
healthy and clinical populations, as well as from various imaging modalities
(sMRI, fMRI, EEG, MEG, PET, etc.). The repository uses modern web technologies
such as interactive web-based visualization, cognitive decoding, and comparison
with other maps to provide researchers with efficient, intuitive tools to
improve the understanding of their results. Each dataset and map is assigned a
permanent Universal Resource Locator (URL), and all of the data is accessible
through a REST Application Programming Interface (API). Additionally, the
repository supports the NIDM-Results standard, and has the ability to parse
outputs from popular FSL and SPM software packages to automatically extract
relevant metadata. This ease of use, modern web-integration, and pioneering
functionality holds promise to improve the workflow for making inferences about
and sharing whole-brain statistical maps.
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