performance

问题 I want to understand the time information on the dumpsys gfxinfo log. It looks like this: Applications Graphics Acceleration Info: Uptime: 16264702 Realtime: 28169900 Can anyone tell me how to associate these figures with System.currentTimeMillis()? 回答1: From ActivityManagerService.java: long uptime = SystemClock.uptimeMillis(); long realtime = SystemClock.elapsedRealtime(); pw.println("Applications Graphics Acceleration Info:"); pw.println("Uptime: " + uptime + " Realtime: " + realtime);

问题 My android studio doesn't responding well. It does not show new Activity option. Even it does not display other option too . I Cleaned and rebuild the project . Even I restart Android studio several times too . Please Help me to solve this issue. 回答1: I ran into this same issue and tried numerous things that I found online but nothing worked. Then I just started trying out random things and when I ran "File -> Sync Project with Gradle files" it started working for me. I can now create

问题 I find myself frequently doing the following: Iterator<A> itr = iterableOfA.getIterator(); List<B> list = new ArrayList<>(); // how about LinkedList? while (itr.hasNext()) { B obj = iter.next().getB(); list.add(obj); } someMethod(list); // this method takes an Iterable I have no idea just how many elements are likely to be in iterableOfA — could be 5, could be 5000. In this case, would LinkedList be a better implementation to use here (since list.add(obj) would then be O(1))? As it stands, if

问题 I find myself frequently doing the following: Iterator<A> itr = iterableOfA.getIterator(); List<B> list = new ArrayList<>(); // how about LinkedList? while (itr.hasNext()) { B obj = iter.next().getB(); list.add(obj); } someMethod(list); // this method takes an Iterable I have no idea just how many elements are likely to be in iterableOfA — could be 5, could be 5000. In this case, would LinkedList be a better implementation to use here (since list.add(obj) would then be O(1))? As it stands, if

问题 I have disassembled a small C++ program compiled with MSVC v140 and am trying to estimate the cycles per instruction in order to better understand how code design impacts performance. I've been following Mike Acton's CppCon 2014 talk on "Data-Oriented Design and C++", specifically the portion I've linked to. In it, he points out these lines: movss 8(%rbx), %xmm1 movss 12(%rbx), %xmm0 He then claims that these 2 x 32-bit reads are probably on the same cache line therefore cost roughly ~200

问题 I have disassembled a small C++ program compiled with MSVC v140 and am trying to estimate the cycles per instruction in order to better understand how code design impacts performance. I've been following Mike Acton's CppCon 2014 talk on "Data-Oriented Design and C++", specifically the portion I've linked to. In it, he points out these lines: movss 8(%rbx), %xmm1 movss 12(%rbx), %xmm0 He then claims that these 2 x 32-bit reads are probably on the same cache line therefore cost roughly ~200

问题 I want to use dynamic table name within a for loop. I understand that there are solutions to this problems by using cursors. But I was wondering if there is a solution without cursor as my current code has generic for loop (implicit cursors) and I wanted to know if I can retain it the same way without going for explicit cursors. What works for me right now is: BEGIN for itr in (select var1,var2,var3,var4 from schedule_table) loop --work using itr.var1, itr.var2, itr.var3, itr.var4 end loop

问题 I'm using Spark for fun and to learn new things about MapReduce. So, I'm trying to write a program suggesting new friendships (i.e., a sort of recommendation system). The suggestion of a friendship between two individuals is performed if they are not connected yet and have a lot of friends in common. The friendship text file has a structure similar to the following: 1 2,4,11,12,15 2 1,3,4,5,9,10 3 2,5,11,15,20,21 4 1,2,3 5 2,3,4,15,16 ... where the syntax is: ID_SRC1<TAB>ID_DST1,ID_DST2,... .

问题 results is 2d numpy array with size 300000 for i in range(np.size(results,0)): if results[i][0]>=0.7: count+=1 it takes me 0.7 second in this python code,but I run this in C++ code,it takes less than 0.07 second. So how to make this python code as fast as possible? 回答1: When doing numerical computation for speed, especially in Python, you never want to use for loops if possible. Numpy is optimized for "vectorized" computation, so you want to pass off the work you'd typically do in for loops

问题 What is the most efficient way to capture screen in python using modules eg PIL or cv2? Because It takes up a lot of ram. I wanted to teach AI to play dino game of Chrome through screen scraping and neat but it is way to slow... I have tried: import numpy as np from PIL import ImageGrab import cv2 import time last_time = time.time() while True: printscreen_pil = ImageGrab.grab(bbox= (0, 40, 800, 640)) printscreen_numpy = np.array(printscreen_pil.getdata(), dtype = 'uint8').reshape(