multithreading

问题 I know that using Thread.Sleep in a task is a dumb idea, because it will block that thread in the thread pool. However, if I have a thread dedicated to something, created by new Thread(new ThreadStart(Foo)) , does Task.Delay still make sense? Nothing is going to use that thread anyhow. I am also wondering what exact effect a Task.Delay will have. It won't put the thread to sleep, so will it act as a spin wait? That would be much worse then a sleep. Wouldn't it be? 回答1: I am having difficulty

问题 I'm writing code using Pandas 0.18/Python 3.5 on an intel i3 (four cores). I have read this: https://www.continuum.io/content/pandas-releasing-gil I also have some work that is IO bound (parsing CSV files into dataframes). I have to do a lot of calculation that is mostly multiplying dataframes. My code is currently parallel using concurrent.futures ThreadPoolExecutor . My question is: In general, should I be using threads to run pandas jobs in parallel, or does pandas make effective use of

问题 I'm writing code using Pandas 0.18/Python 3.5 on an intel i3 (four cores). I have read this: https://www.continuum.io/content/pandas-releasing-gil I also have some work that is IO bound (parsing CSV files into dataframes). I have to do a lot of calculation that is mostly multiplying dataframes. My code is currently parallel using concurrent.futures ThreadPoolExecutor . My question is: In general, should I be using threads to run pandas jobs in parallel, or does pandas make effective use of

问题 does offer blocks poll or vice versa ? meaning , can a producer offer and at the same time a consumer trying to poll ? or if a producer was offering , the queue blocks till he is done ? object A while (true){ inputQueue.offer(newPartList); } object B while (true){ inputQueue.poll(newPartList); } 回答1: No, it does not. use LinkedBlockingDeque instead. Remember to use methods from BlockingDequeue or BlockingQueue interfaces to get values. as these methods are implemented as blocking. Update

问题 I have a question regarding the use of BLAS parallelized matrix product in R (being the default matrix product at least since R-3.4, maybe earlier). The default behavior (at least on my machine) is now for the matrix product (c.f. example below) to use all the cores available on the machine, which can be a problem. Do you know how to control the number of cores used for standard matrix product in R? Thanks in advance Example: n=10000 p=1000 q=5000 A = matrix(runif(n*p),nrow=n, ncol=p) B =

问题 I'm trying to make client program that communicates with a server using a TcpStream wrapped by a openssl::ssl::SslStream (from crates.io). It should wait for read , and process data sent from the server if it was received without delay . At the same time, it should be able to send messages to the server regardless of reading. I tried some methods such as Passing single stream to both read and write threads. Both read and write methods require a mutable reference, so I couldn't pass a single

问题 Today I read some blogs and source code about how Handler & Looper work together. Based on what I've learnt, we can have only one Looper on each thread by using the ThreadLocal magic. Usually Handler is initiated in main thread, or else you must manually start or saying, prepare the Looper on a separate thread and then loop it up. class LooperThread extends Thread { public Handler mHandler; public void run() { Looper.prepare(); mHandler = new Handler() { public void handleMessage(Message msg)

问题 Today I read some blogs and source code about how Handler & Looper work together. Based on what I've learnt, we can have only one Looper on each thread by using the ThreadLocal magic. Usually Handler is initiated in main thread, or else you must manually start or saying, prepare the Looper on a separate thread and then loop it up. class LooperThread extends Thread { public Handler mHandler; public void run() { Looper.prepare(); mHandler = new Handler() { public void handleMessage(Message msg)

问题 I am writing a Python program where in the main thread I am continuously (in a loop) receiving data through a TCP socket, using the recv function. In a callback function, I am sending data through the same socket, using the sendall function. What triggers the callback is irrelevant. I've set my socket to blocking. My question is, is this safe to do? My understanding is that a callback function is called on a separate thread (not the main thread). Is the Python socket object thread-safe? From

问题 I am writing a Python program where in the main thread I am continuously (in a loop) receiving data through a TCP socket, using the recv function. In a callback function, I am sending data through the same socket, using the sendall function. What triggers the callback is irrelevant. I've set my socket to blocking. My question is, is this safe to do? My understanding is that a callback function is called on a separate thread (not the main thread). Is the Python socket object thread-safe? From