Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality. Learn more →
Top 23 Memory Open-Source Projects
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
memreduct
Lightweight real-time memory management application to monitor and clean system memory on your computer.
-
MTuner
MTuner is a C/C++ memory profiler and memory leak finder for Windows, PlayStation 4 and 3, Android and other platforms
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
iGlance
Free system monitor for OSX and macOS. See all system information at a glance in the menu bar.
-
rpmalloc
Public domain cross platform lock free thread caching 16-byte aligned memory allocator implemented in C
-
WinMemoryCleaner
This free RAM cleaner uses native Windows features to optimize memory areas. It's a compact, portable, and smart application.
-
memory
STL compatible C++ memory allocator library using a new RawAllocator concept that is similar to an Allocator but easier to use and write.
-
stress-ng
This is the stress-ng upstream project git repository. stress-ng will stress test a computer system in various selectable ways. It was designed to exercise various physical subsystems of a computer as well as the various operating system kernel interfaces.
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
I collected a list of profilers (also memory profilers, also specifically for Python) here: https://github.com/albertz/wiki/blob/master/profiling.md
Currently I actually need a Python memory profiler, because I want to figure out whether there is some memory leak in my application (PyTorch based training script), and where exactly (in this case, it's not a problem of GPU memory, but CPU memory).
I tried Scalene (https://github.com/plasma-umass/scalene), which seems to be powerful, but somehow the output it gives me is not useful at all? It doesn't really give me a flamegraph, or a list of the top lines with memory allocations, but instead it gives me a listing of all source code lines, and prints some (very sparse) information on each line. So I need to search through that listing now by hand to find the spots? Maybe I just don't know how to use it properly.
I tried Memray, but first ran into an issue (https://github.com/bloomberg/memray/issues/212), but after using some workaround, it worked now. I get a flamegraph out, but it doesn't really seem accurate? After a while, there don't seem to be any new memory allocations at all anymore, and I don't quite trust that this is correct.
There is also Austin (https://github.com/P403n1x87/austin), which I also wanted to try (have not yet).
Somehow this experience so far was very disappointing.
(Side node, I debugged some very strange memory allocation behavior of Python before, where all local variables were kept around after an exception, even though I made sure there is no reference anymore to the exception object, to the traceback, etc, and I even called frame.clear() for all frames to really clear it. It turns out, frame.f_locals will create another copy of all the local variables, and the exception object and all the locals in the other frame still stay alive until you access frame.f_locals again. At that point, it will sync the f_locals again with the real (fast) locals, and then it can finally free everything. It was quite annoying to find the source of this problem and to find workarounds for it. https://github.com/python/cpython/issues/113939)
Project mention: What is the appropriate uncompressed kernel ELF to use with dwarf2json? [ 5.19.0-42-generic #43~22.04.1-Ubuntu ], in order to create generate a custom symbols table to conduct linux memory forensics on Ubuntu 22.04? | /r/computerforensics | 2023-05-28I need this to create generate a custom symbols table (using dwarf2json), in order to run a memory dump acquired by Ubuntu 22.04, as Ubuntu 22.04 kernel does not work anymore with volatility 2 (Issue here: volatilityfoundation/volatility#828)
Project mention: Recently during games my cpu goes to 100% and i barely get 30fps on games that used to run at 60fps easily. | /r/nvidia | 2023-07-18Simply put: Memreduct is an app that cleans up processes and memory to help improve FPS.
Project mention: 10 Powerful Node.js Libraries Every Developer Should Know About | dev.to | 2023-04-274. node-cache
For note-taking specifically, I've tried everything from plain old pen and paper to more modern solutions like Evernote and emacs (if you can call that modern), but nothing I've come across really beats Anki.
Although its main selling point is as a program for flashcards with spaced repetition, it comes with pretty much all the features of a good note-taking app, like tags, easy to organize, synchronization across devices (you can set up your own server), good interface for searching through your notes (which are stored in an Sqlite db if that matters), and yes, LaTeX. Not only that, it's also highly extendable with third-party plugins, so if there are features that you miss chances are there's a plugin for it. In other words, you can use it perfectly fine just taking notes. However, where it really shines is in all of this in combination the spaced repetition algorithm, which is now on steroids with FSRS[1][2]. The downside is that for this to be effective for the things you want to memorize, you'll have to write your notes to be suitable for a flashcard, but if you do it consistently you'll soon notice that you can store most of your notes in your head (needless to say, any student would greatly benefit from this). Now, if that's too much work, you can still just use the scheduling to have it remind you of your notes. Either way, even as someone who sometimes goes out of his way to shoehorn everything into Emacs, I can't see a reason not to use anki for note-taking.
[1]https://github.com/open-spaced-repetition/fsrs4anki/blob/mai...
[2]https://www.youtube.com/watch?v=OqRLqVRyIzc
In term of automatically saving everything, There is heyday.xyz, polished but quite expensive. Or https://github.com/karlicoss/promnesia, a more experimental take.
Project mention: Why is it using that much ram? Is that a trojan? Is that a feature of the linux-tkg kernel? (nothing else is running in the background) | /r/linuxmasterrace | 2023-07-01I use a script I call memtop10.sh that uses a combination of ps and ps_mem.py which you can find here: https://github.com/pixelb/ps_mem/blob/master/ps_mem.py
Memory related posts
- Show HN: In memory Rust database to query your data like a Venn diagram
- Show HN: In memory Rust database to query your data like a Venn diagram
- Embeddable, Distributed In-Memory datastore compatible with Redis clients
- Nuke v1.3.0 – A memory arena implementation for Go
- Nuke v1.1.0 – A memory arena implementation for Go
- Nuke 1.0.1 – A memory arena implementation for Go
- Memray – A Memory Profiler for Python
-
A note from our sponsor - InfluxDB
www.influxdata.com | 24 Apr 2024
Index
What are some of the best open-source Memory projects? This list will help you:
Project | Stars | |
---|---|---|
1 | memray | 12,510 |
2 | psutil | 9,905 |
3 | volatility | 6,910 |
4 | memreduct | 5,121 |
5 | memlab | 4,171 |
6 | sysstat | 2,869 |
7 | MTuner | 2,547 |
8 | memguard | 2,484 |
9 | iGlance | 2,403 |
10 | gocache | 2,221 |
11 | volatility3 | 2,197 |
12 | node-cache | 2,196 |
13 | fsrs4anki | 2,177 |
14 | rpmalloc | 2,010 |
15 | easydeviceinfo | 1,752 |
16 | Mesh | 1,702 |
17 | promnesia | 1,686 |
18 | memfs | 1,606 |
19 | ps_mem | 1,507 |
20 | WinMemoryCleaner | 1,476 |
21 | memory | 1,436 |
22 | stress-ng | 1,423 |
23 | observer_cli | 1,344 |
Sponsored