First, note that Go, itself, doesn’t always shrink its own memory space: https://groups.google.com/forum/#!topic/Golang-Nuts/vfmd6zaRQVs The heap is freed, you can check this using runtime.ReadMemStats(), but the processes virtual address space does not shrink — ie, your program will not return memory to the operating system. On Unix based platforms we use a system call to tell … Read more
For now, this is the best way. this.setState(previousState => ({ myArray: […previousState.myArray, ‘new value’] }));
I created a complete function based on the answer of FabrÃcio Pereira. def get_model_memory_usage(batch_size, model): import numpy as np try: from keras import backend as K except: from tensorflow.keras import backend as K shapes_mem_count = 0 internal_model_mem_count = 0 for l in model.layers: layer_type = l.__class__.__name__ if layer_type == ‘Model’: internal_model_mem_count += get_model_memory_usage(batch_size, l) single_layer_mem … Read more
On some 32bit systems PHP will take the memory settings like 2000M or 2G and convert it to the integer number of bytes by not performing a boundary check. A number starting at 2G or 2048M will be -2147483648 bytes then. Some PHP versions cap this at the top, so it won’t go into negative … Read more
I’m surprised: Figure 3 in the middle of this article, The Pathologies of Big Data, says that memory is only about 6 times faster when you’re doing sequential access (350 Mvalues/sec for memory compared with 58 Mvalues/sec for disk); but it’s about 100,000 times faster when you’re doing random access.
The most common way to determine the deepest stack usage is to initialize the stack memory with some known but unusual value, then periodically (or at the end of a big test run) see where that pattern stops. This is exactly how the IAR IDE determines the amount of stack used.
After a lot of playing around and testing different ideas, some of which were mentioned here, the final solution that worked for me was as follows. Instead of creating new MKMapView’s as needed in the app, I added an mkMapView property to my AppDelegate and only created it when needed. Once it has been created, … 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
some time ago I stole this little nugget from here: sort( sapply(ls(),function(x){object.size(get(x))})) it has served me well