jit

问题 I have this python code that should run just fine. I'm running it on Anaconda's Spyder Ipython console, or on the Anaconda terminal itself, because that is the only way I can use the "numba" library and its "jit" decorator. However, either one always "freezes" or "hangs" just about whenever I run it. There is nothing wrong with the code itself, or else I'd get an error. Sometimes, the code runs all the way through perfectly fine, sometimes it just prints the first line from the first function

问题 Say I run a Python (2.7, though I'm not sure that makes a difference here) script. Instead of terminating the script, I tab out, or somehow switch back to my editing environment. I can then modify the script and save it, but this changes nothing in the still-running script. Does Python load all source files into memory completely at launch? I am under the impression that this is how the Python interpreter works, but this contradicts my other views of the Python interpreter: I have heard that

问题 What is the loop unrolling policy for JIT? Or if there is no simple answer to that, then is there some way i can check where/when loop unrolling is being performed in a loop? GNode child = null; for(int i=0;i<8;i++){ child = octree.getNeighbor(nn, i, MethodFlag.NONE); if(child==null) break; RecurseForce(leaf, child, dsq, epssq); } Basically, i have a piece of code above that has a static number of iterations (eight), and it does bad when i leave the for loop as it is. But when i manually

问题 What is the loop unrolling policy for JIT? Or if there is no simple answer to that, then is there some way i can check where/when loop unrolling is being performed in a loop? GNode child = null; for(int i=0;i<8;i++){ child = octree.getNeighbor(nn, i, MethodFlag.NONE); if(child==null) break; RecurseForce(leaf, child, dsq, epssq); } Basically, i have a piece of code above that has a static number of iterations (eight), and it does bad when i leave the for loop as it is. But when i manually

问题 We are building a tool for average case runtime analysis of Java Byte Code programs. One part of this is measuring real runtimes. So we would take an arbitrary, user provided method that may or may not have a result and may or may not have side effects (examples include Quicksort, factorial, dummy nested loops, ...) and execute it (using reflection), measuring the elapsed time. (Whether or not we benchmark properly at all is besides the point here.) In the benchmarking code, we obviously don

问题 I've found that one of my application posted on the market produces weird results on some phones. Upon investigation it turns out there is an issue with one function which computes distance between two GeoPoints - sometimes it returns completely wrong value. This issue reproduces only on devices with MediaTek MT6589 SoC (aka MTK6589). And AFAIK all of such devices have Android 4.2 installed. Update I was also able to reproduce the bug on Lenovo S6000 tablet with MediaTek MT8125/8389 chip and

问题 One of the new performance enhanchements for .NET 4.5 is the introduction of the 'MultiCode JIT'. See here for more details. I have tried this, but it seems to have no effect on my application. The reason why I am interested is that my app (IronScheme) takes a good long time to startup if not NGEN'd, which implies a fair amount of JIT'ng is involved at startup. (1.4 sec vs 0.1 sec when NGEN'd). I have followed the instructions on how to enable this, and I can see a 'small' (4-12KB) is created

问题 When we remote a method (that is using generics) the remoting sink cannot seem to discover our method from the other identical named ones. Debugging with .net source code attached I've got it to where there is a MethodInfo.MakeGenericMethod call. However I cannot look at any of the surrounding data as its been jit optimised. I couple of weeks ago I came across a registry setting that would disable this setting (it specifically mentioned that it aid debugging with the source). However being a

问题 When I read about the performance of JITted languages like C# or Java, authors usually say that they should/could theoretically outperform many native-compiled applications. The theory being that native applications are usually just compiled for a processor family (like x86), so the compiler cannot make certain optimizations as they may not truly be optimizations on all processors. On the other hand, the CLR can make processor-specific optimizations during the JIT process. Does anyone know if

问题 I have heard that Java must use a JIT to be fast. This makes perfect sense when comparing to interpretation, but why can't someone make an ahead-of-time compiler that generates fast Java code? I know about gcj , but I don't think its output is typically faster than Hotspot for example. Are there things about the language that make this difficult? I think it comes down to just these things: Reflection Classloading What am I missing? If I avoid these features, would it be possible to compile