cpu

问题 I'm running this command grep 'cpu ' /proc/stat | awk '{usage=($2+$4)*100/($2+$4+$5)} END {print usage "%"}' Yet it only outputs something like 0.99xxxx% If I do an apt-get upgrade or any process, I would imagine it would go above 1%. Even running stress -c 1 doesn't make it change any. Is there a way to log CPU usage accurately? Server has 1 vCPU. Need to have this log every 5 seconds. while sleep 5; do "code" >> logfile; done 回答1: Why does cpu load not change more than a few hundredths?

问题 I can find the latencies in terms of either ns or CPU cylces between CPU core and its cache, main memory, etc. But it seems so hard to find similiar information about modern GPU. Does anyone know about the latencies of GPU, esepecially the latencies between modern nvidia GPU (GF110 or later) and their memory, thanks. GPU memory do have a much larger bandwidth, but what about their latencies? I heard that the latencies for GPU are just as high as these for CPU, so basically make the larger

问题 I keep getting the CPU-debug window in D2010 IDE, i noticed this appears on some Breakepoints, some others doesnt cause this effect. Can't explain when exactly this happends or which Breakpoints cause this but it seems like when the debugger can't reach a breackpoint on code it stops on the beginaddress of the method, and it gets in an endless loop so even removing the Breakpoint doesnt help, only solution is break debugging, remove breakpoint and restart again. I had the same issue with D7

问题 I have written come code that has worked on both Windows XP and Windows Server 2008 64-Bit. However I have just launched an Amazon Windows 64-bit instance and the code fails. Very simple it looks like this import multiprocessing processors = multiprocessing.cpu_count() print processors I receive a NotImplementedError which I do not understand and the docs are not that helpful in explaining. I just do not understand why it would work on one server and not on another with identical

问题 One of my c++ application shows very high %CPU in top, but the load is quite low. myapp always takes around 30%, showing at the very top of the "top" command, but the load is always like 0.00, so I'm confused what are the differences between load and %CPU column? top - 14:09:54 up 62 days, 2:52, 1 user, load average: 0.00, 0.00, 0.00 Tasks: 124 total, 1 running, 123 sleeping, 0 stopped, 0 zombie Cpu0 : 0.0%us, 0.0%sy, 0.0%ni, 99.7%id, 0.3%wa, 0.0%hi, 0.0%si, 0.0%st Cpu1 : 0.0%us, 0.0%sy, 0.0

问题 Is there any small tool that gives me access to the data gathered by the Intel CPU Counters (like L1/L2 cache misses, branch prediction failures ... you know there are hunderts of them on modern Core2 CPU's). It must work on Windows (while being able to use it with Solaris, FreeBSD, Linux, MacOSX would of course be nice). 回答1: This thread seems a little old but if you're still interested, I wrote a howto recently on this topic using nothing more than rdmsr and wrmsr in Linux. It only deals

问题 I have done a sched_setaffinity test in Linux in a server with 1 socket ,4 cores , the following /proc/cpuinfo showes the cpu information : processor : 0 model name : Intel(R) Core(TM)2 Quad CPU Q8400 @ 2.66GHz cache size : 2048 KB physical id : 0 siblings : 4 cpu cores : 4 processor : 1 model name : Intel(R) Core(TM)2 Quad CPU Q8400 @ 2.66GHz cache size : 2048 KB physical id : 0 siblings : 4 cpu cores : 4 processor : 2 model name : Intel(R) Core(TM)2 Quad CPU Q8400 @ 2.66GHz cache size :

问题 I have 700 items and I loop through the 700 items for each I obtain the item' three attributes and perform some basic calculations. I have implemented this using two techniques: 1) Three 700-element arrays, one array for each of the three attributes. So: item0.a = array1[0] item0.b = array2[0] item0.e = array3[0] 2) One 2100-element array containing data for the three attributes consecutively. So: item0.a = array[(0*3)+0] item0.b = array[(0*3)+1] item0.e = array[(0*3)+2] Now the three item

问题 I'm noticing that my django development server (version 1.1.1) on my local windows7 machine is using a lot of CPU (~30%, according to task manager's python.exe entry), even in idle state, i.e. no request coming in/going out. Is there an established way of analysing what might be responsible for this? Thanks! Martin 回答1: FWIW, you should do the profiling, but when you do I'll bet you find that the answer is "polling for changes to your files so it can auto-reload." You might do a quick test

问题 I have long wondered what is more efficient with regards to making better use of CPU caches (which are known to benefit from locality of reference) - two loops each iterating over the same mathematical set of numbers, each with a different loop body, or having one loop that "concatenates" the two bodies into one, and thus accomplishes identical total result, but all in itself? In my opinion, having two loops would introduce fewer cache misses and evictions because more instructions and data