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Arraysync slide show how to#
All that remained was to learn how to use it and how to seamlessly integrate it in a traditional Windows-based APL application. The first step was the choice of the tools and so we went fishing and caught in our net D3.js, a very versatile open source JavaScript library for manipulating web documents based on data. We identified a few areas where the introduction of charts would improve significantly the user experience and set off on their implementation. Instead of trying to compete with dedicated reporting tools, we thought we would play to our strengths if we concentrated on a handful of tailored charts. A short while ago we decided that the time was ripe for it to start drawing pictures to better show the beauty of those numbers. Sofia, our portfolio management system for institutional investors, is capable of producing large quantities of numbers. Certainly, most human beings find an interactive chart more intuitive than a table with a thousand numeric rows. They say that a picture is worth a thousand words. Robert Bernecky, Snake Island Research (Canada) U08: A Compendium of SIMD Boolean Array Algorithms in APL summary | slides (3.4 MB) | handouts (3.7 MB) | video (45 mins) The Futhark compiler performs a number of GPU-critical optimisations before outputting GPU-optimised OpenCL code, which will be shown to integrate well with host-executed implementations of high-level languages, such as Python or even an APL interpreter. The compiler infrastructure compiles APL programs into programs written in a typed array intermediate language (called TAIL), which are then recompiled into programs written in the functional array programming language, Futhark. He will reflect on the programmer's experience with programming in the supported, statically typeable, subset of APL and the fact that the compiler infrastructure does not necessarily embrace the use of idioms before inviting APL programmers to reproduce the obtained results he will also invite experienced APL programmers to improve on the implementation of the Dyalog versions of the benchmarks and to provide feedback about which additional APL features should be considered indispensable.
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He demonstrates that, for a number of benchmarks, the generated GPU programs runs in the order of 100x faster than compiled generated C code running on similarly-priced CPU hardware. Likewise, any image-editing software, on opening a file and decompressing it (if necessary) to make it editable should also orient it first.Martin presents a compiler infrastructure for compiling a subset of APL, written in the style of co-dfns, into performance efficient GPU programs.
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Arraysync slide show software#
Two images, one in the same rotation as the image-sensor array in the iPhone and the other rotated, have their Orientation value tagged in EXIF data.Īny software that can display an image should be able to read this orientation flag and display a photo in the correct orientation. (Rotations that aren’t aren’t at right angles always involves modifying image data to approximate the new angle.) Eight different orientations can be represented with a value for the EXIF Orientation tag. The orientation flag has one of eight values, representing each rotation of 0 degrees, 90 degrees, 180 degrees, and 270 degrees, as well as mirror flips (flipped top to bottom and left to right, and clockwise rotated top to bottom and left to right). The trick that camera makers came up with was to avoid rotating pixels and, instead, set a flag in the EXIF metadata that’s incorporated in any image their camera exports. Not all cameras had the perfect units years ago, and not all still do.īut if a camera (or other software) rotates a JPEG after it’s been saved in that format, each decompression, rotation, and recompression It’s possible to rotate JPEGs without adding additional image quality loss if the image resolutionĭivides perfectly into the 8 by 8 or 16 by 16 grids that a given JPEG algorithm used. (“Lossless” compression is less efficient, but by identifying redundant patterns in a hunk of data, it allows an exact reproduction of the original data from the compressed file.) “Lossy” file formats like JPEG use approximations via mathematical formats to describe regions of an image some camera makers’ raw formats are lossy as well. If the camera were to produce with data stored in the same orientation as you took the picture, except for the single orientation that matches how data comes out of the sensor array, it would need to create a second image file into which to map each pixel from one orientation to the other, then delete that original file.Įarlier cameras lacked the computational power to handle this rotation, which was also RAM intensive: The image would need to be rotated before the sensor data was converted to a file format that compressed image data, like JPEG.