Because 32 bits are able to represent numbers up to 232 − 1 = 4294967295 = 4 GiB − 1 and therefore address up to 232 individual bytes which would be 4 GiB then. There are ways to circumvent that, though. For example using PAE even a 32-bit operating system can support more memory. Historically … Read more
Ok, based on the book Modern Operating Systems 3rd Edition by Andrew S. Tanenbaum and the materials form Open Security Training (opensecuritytraining.info), i manage to understand the segmentation and paging and the answer for my question is: Concepts: 1.1.Segmentation: Segmentation is the division of the memory into pieces (sections) called segments. These segments are independents … Read more
The max_split_size_mb configuration value can be set as an environment variable. The exact syntax is documented at https://pytorch.org/docs/stable/notes/cuda.html#memory-management, but in short: The behavior of caching allocator can be controlled via environment variable PYTORCH_CUDA_ALLOC_CONF. The format is PYTORCH_CUDA_ALLOC_CONF=<option>:<value>,<option2>:<value2>… Available options: max_split_size_mb prevents the allocator from splitting blocks larger than this size (in MB). This can help … Read more
In the etc directory under your Netbeans-Home, edit the file netbeans.conf file. -Xms and -Xmx should be increased to the values that allow your program to compile. Here are the instructions in netbeans.conf: # Note that default -Xmx and -XX:MaxPermSize are selected for you automatically. # You can find these values in var/log/messages.log file in … Read more
Depends on what exactly you want to use it for. If you want to map existing files into memory, that’s supported with memory-mapped files. They can also be used to share memory between processes (use named mapping object with no underlying file). If you want to map physical memory, that’s generally not supported from user … Read more
When we use cudaMalloc() In order to store data on the gpu that can be communicated back to the host, we need to have alocated memory that lives until it is freed, see global memory as the heap space with life until the application closes or is freed, it is visible to any thread and … Read more
Stack: The stack is used as a sort of temporary scratch pad for use by the block of code that’s currently executing, and whatever block called the current one, and whatever block called that one, and so on. When the current block exits, the local variables it was using are forgotten. As the name indicates, … Read more
Not a complete solution – but a potential approach, based on the ‘guard’. Start make with high ‘-j’ value. Run a guard job that a. Wait for thrashing (page fault/second above a limit), and high CPU utilization. b. Find the jobs with the highest memory usage, suspend it. c. Wait for some time to allow … Read more
It depends on what you’re doing. With functional programming you don’t have to create defensive copies, so for certain problems it can end up using less memory. Many functional programming languages also have good support for laziness, which can further reduce memory usage as you don’t create objects until you actually use them. This is … Read more
It is all the same physical memory. The difference is who is controlling it. The Microsoft definition is that managed memory is cleaned up by a Garbage Collector (GC), i.e. some process that periodically determines what part of the physical memory is in use and what is not. Unmanaged memory is cleaned up by something … Read more