One of the most common errors that I found developing Android Apps is the “java.lang.OutOfMemoryError: Bitmap Size Exceeds VM Budget” error. I found this error frequently on activities using lots of bitmaps after changing orientation: the Activity is destroyed, created again and the layouts are “inflated” from the XML consuming the VM memory available for … Read more
Since you are running Spark in local mode, setting spark.executor.memory won’t have any effect, as you have noticed. The reason for this is that the Worker “lives” within the driver JVM process that you start when you start spark-shell and the default memory used for that is 512M. You can increase that by setting spark.driver.memory … Read more
A copy constructor is used to initialize a previously uninitialized object from some other object’s data. A(const A& rhs) : data_(rhs.data_) {} For example: A aa; A a = aa; //copy constructor An assignment operator is used to replace the data of a previously initialized object with some other object’s data. A& operator=(const A& rhs) … Read more
What is the maximum amount of memory (in Megabytes / as percentage of the total RAM) that an Android application (that is not a system app) can use? That varies by device. getMemoryClass() on ActivityManager will give you the value for the device your code is running upon. Are there any differences between the Android … Read more
The built-in process module has a method memoryUsage that offers insight in the memory usage of the current Node.js process. Here is an example from in Node v0.12.2 on a 64-bit system: $ node –expose-gc > process.memoryUsage(); // Initial usage { rss: 19853312, heapTotal: 9751808, heapUsed: 4535648 } > gc(); // Force a GC for … Read more
Scala makes it very easy to use enormous amounts of memory without realizing it. This is usually very powerful, but occasionally can be annoying. For example, suppose you have an array of strings (called array), and a map from those strings to files (called mapping). Suppose you want to get all files that are in … Read more
Reducing memory usage in Python is difficult, because Python does not actually release memory back to the operating system. If you delete objects, then the memory is available to new Python objects, but not free()‘d back to the system (see this question). If you stick to numeric numpy arrays, those are freed, but boxed objects … Read more
Results of testing with the utility Split wrote (link is in his answer): device: (crash amount/total amount/percentage of total) iPad1: 127MB/256MB/49% iPad2: 275MB/512MB/53% iPad3: 645MB/1024MB/62% iPad4: 585MB/1024MB/57% (iOS 8.1) iPad Mini 1st Generation: 297MB/512MB/58% iPad Mini retina: 696MB/1024MB/68% (iOS 7.1) iPad Air: 697MB/1024MB/68% iPad Air 2: 1383MB/2048MB/68% (iOS 10.2.1) iPad Pro 9.7″: 1395MB/1971MB/71% (iOS 10.0.2 … Read more
There are a few operations on Tensors in PyTorch that do not change the contents of a tensor, but change the way the data is organized. These operations include: narrow(), view(), expand() and transpose() For example: when you call transpose(), PyTorch doesn’t generate a new tensor with a new layout, it just modifies meta information … Read more
You can use the java.lang.instrumentation package. It has a method that can be used to get the implementation specific approximation of object size, as well as overhead associated with the object. The answer that Sergey linked has a great example, which I’ll repost here, but you should have already looked at from his comment: import … Read more