Obviously for parallel code and dense linear algebra it does rather better, more like 2x as fast overall. But that's being very specific in limiting code to non-vectorized non-parallelized. The new iMac is likewise maybe 50% faster than its predecessor (so that's 4.2GHz Xeon W 2017 vs 3.6GHz Haswell 2012), about the same sort jump as the A10X to A12X. Frequency jumped very little, so this is mostly better IPC, presumably mostly from better memory system. Summarizing things to a single number, the A12X is about 50% faster than the A10X, and most of the time this is not the result of the extra core. Not really, the conclusion is much the same as last year. Perhaps the byte code is optimized differently in the app store for the two different cores, and there's a very specific bug in the A10X optimization path that's rarely triggered, and that Apple hasn't yet fixed ?)Īnyway it's still slightly irritating working with Player, and trying to benchmark, on the A12X, but much better than before.Īpart from that, is there anything specifically interesting to report? (It could be hitting memory limits on the A10X, but it doesn't look like that - the memory monitor doesn't show a wild spike to 100% RAM.
The app is definitely a lot more stable, and on the A12X iPad Pro, it's even more stable. So given all that weirdness, same as before, has anything improved? (I would not expect them to waste time trying to ship work to the small cores.) Who knows what's going on, but it seems like some of the code is set up to correctly query the OS for the number of cores while the rest of the code is locked to a max of three cores from the old iPad? So maybe Wolfram is randomly (on launch) A/B testing a better bignum library?Īnother thing that is performance-relevant strange is that for the few places where Wolfram does automatically parallelize, they seem to parallelize more often than not to three rather than four cores. There is one strange thing, in that when I ran the large integer multiplication tests, almost always I got the slow results I would expect, but one occasion (repeatable within that kernel launch session) the numbers were about 4x faster. It's not clear that any of this has large-scale improved over the past year (and three Wolfram Player update). not providing vector support for some stuff that is vectorized on x86 not parallelizing a lot of code that is parallelized on x86 (though they parallelize some, and it's kinda weird what is and is not)
not using an efficient bignum library (for ints or reals) Recall that this is a test of Wolfram Player on the iPad, and Mathematica on x86.Īs before, the most prominent immediate feature is that Wolfram are very definitely wolfram.Now that I have an iPad Pro, I reran my benchmarks on the new iPad and an iMac Pro.
#TESTING WOLFRAM PLAYER FOR FREE#
Wolfram Notebooks are viewable for free with Wolfram Player. languageĮxplore the author's Wolfram Notebooks and look for updates in Coursera and Wolfram U for use with this book wolfr.am/klopper Unique in its approach of having vast built-in knowledge and automation, the Wolfram Language scales from a single line of easy-to-understand interactive code to million-line production systems. The Wolfram Language represents a major advance in programming languages that makes leading edge computation accessible to everyone.
#TESTING WOLFRAM PLAYER HOW TO#
Follow along as Klopper offers step-by-step instructions and relevant exercises from the field of medical statistics designed to teach readers how to understand and present data in today's increasingly data-driven world. Topics include descriptive statistics, distributions, hypothesis testing, parametric testing, correlation and much more. Starting from the basics and working through a range of foundational concepts, Klopper shows just how accessible computational statistics canīe given the appropriate tool set. Introduction to Statistics with the Wolfram Language applies the extensive computational power of the Wolfram Language to the field of statistics.
0 kommentar(er)
