shared-memory

Can someone explain why ashmem was created? I'm browsing through mm/ashmem.c right now. As near as I can tell, the kernel is thinking of ashmem as file-backed memory that can be mmap'd. But then, why go to the trouble of implementing ashmem? It seems like the same functionality could be achieved by mounting a RAM fs and then using filemap/mmap to share memory. I'm sure that ashmem can do more fancy stuff -- from looking at the code, it seems to have something to do with pinning/unpinning pages? Ashmem allows processes which are not related by ancestry to share memory maps by name, which are

Is there a Python module that would enable me to place instances of non-trivial user classes into shared memory? By that I mean allocating directly in shared memory as opposed to pickling into and out of it. multiprocessing.Value and multiprocessing.Array wouldn't work for my use case as they only seem to support primitive types and arrays thereof. The only thing I've found so far is POSH , but it hasn't changed in eight years. This suggests that it's either super-stable or is out of date. Before I invest time in trying to get it work, I'd like to know if there are alternatives I haven't

I use openssl_pkcs7_sign and openssl_pkcs7_encrypt to create encrypted data. The functions only accept file names. I would like to store the temporary files in shared memory to improve performance. I understand in Linux I can file_put_contents('/dev/shm/xxx', data) , but it is not possible for Windows. Is there portable way in PHP to do this? Would shmop_ function help here? Thanks. PS: Or is there way to make these functions accept data strings? PS2: Please do not suggest invoking /usr/bin/openssl from PHP. It is not portable. Since Windows 2000, the shmop (previously shm_ ) methods are

I would like to use a queue for passing data from a parent to a child process which is launched via multiprocessing.Process . However, since the parent process uses Python's new asyncio library, the queue methods need to be non-blocking. As far as I understand, asyncio.Queue is made for inter-task communication and cannot be used for inter-process communication. Also, I know that multiprocessing.Queue has the put_nowait() and get_nowait() methods but I actually need coroutines that would still block the current task (but not the whole process). Is there some way to create coroutines that wrap

I am aware of several questions and answers on this topic, but haven't found a satisfactory answer to this particular problem: What is the easiest way to do a simple shared-memory parallelisation of a python loop where numpy arrays are manipulated through numpy/scipy functions? I am not looking for the most efficient way, I just wanted something simple to implement that doesn't require a significant rewrite when the loop is not run in parallel. Just like OpenMP implements in lower level languages. The best answer I've seen in this regard is this one , but this is a rather clunky way that

Having learnt a bit about the subject, can anyone tell, what is the real difference between POSIX shared memory (shm_open) and POSIX mapped files (mmap)? Both seems to use the /dev/tmpfs subsystem, rather then older IPC mechanism. So is there any advantage of using mmap file over shared memory? Thanks. The distinction is not always clear. Shared memory can be implemented via memory mapped files. An excellent write on this can be found here (as applied to C/C++ programming). My understanding is that that shared memory is built on top of mapped files, but This Page seems to indicate that the