After spending awhile last Friday trying to vectorize a loop of a small matrix-vector multiplication for every pixel of an image, I gave up and decided to just write it as a DLM. For my image sizes of 1024 by 1024 pixels (actually two images of that size), the run time went from 3.15 seconds to 0.26 seconds on my MacBook Pro. That’s not a lot of time to save, but since we acquire imagery every 15 seconds, it was useful.
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Modern IDL offers IDL programmers one place to look for explanation, techniques, and reference material, for beginners and advanced users alike.
"... But I've always wanted a thorough, concise, up-to-date overview of the the IDL language and its vast capabilities. This is exactly what Mike's book provides in 464 very informative pages... Highly recommended!"
I'm a software developer focusing on high-performance computing and visualization in scientific programming. I work mostly in IDL, but occasionally use C, CUDA, and Python.
I currently work for the National Center for Atmospheric Research (NCAR) at the Mauna Loa Solar Observatory. Previously, I worked for Tech-X Corporation, where I was the main developer for GPULib, a library of IDL bindings for GPU accelerated computation routines.
Need consulting/instruction? Contact me.
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