shumai
Memcached
shumai | Memcached | |
---|---|---|
15 | 56 | |
1,122 | 13,208 | |
0.2% | 0.7% | |
2.2 | 8.4 | |
9 months ago | about 15 hours ago | |
TypeScript | C | |
MIT License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
shumai
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PyTorch Primitives in WebGPU for the Browser
https://github.com/tensorflow/tfjs/tree/master/tfjs-backend-...
([...], tflite-support, tflite-micro)
From facebookresearch/shumai (a JS tensor library) https://github.com/facebookresearch/shumai/issues/122 :
> It doesn't make sense to support anything besides WebGPU at this point. WASM + SIMD is around 15-20x slower on my machine[1]. Although WebGL is more widely supported today, it doesn't have the compute features needed for efficient modern ML (transformers etc) and will likely be a deprecated backend for other frameworks when WebGPU comes online.
tensorflow rust has a struct.Tensor:
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Why do people curse JS so much, but also say it's better than Python
JS for ML actually does exist https://github.com/facebookresearch/shumai
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Breaking Up with Python
> It's really a shame that data science, ML, and notebooks are so wrapped up in it. Otherwise we could jettison the whole thing into space
Although I personally feel Python has its place, I contribute to a project that hopes to diversify the ML/scientific computing space with a TypeScript tensor lib called Shumai: https://github.com/facebookresearch/shumai
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Tinygrad: A simple and powerful neural network framework
Doesn’t really matter for large batch/large model training on GPUs that don’t need much coordination.
But Python speed is one of the main motivations for a JS/TS based ML lib I’m working on: https://github.com/facebookresearch/shumai
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[D] Using JavaScript for ML Training/Research (not in the browser)
As a hedge against CPython never becoming fast, we're creating a project called Shumai that attempts to deeply integrate with a new JavaScript runtime (Bun[3]).
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Python 3.11 is much faster than 3.8
You can expose objects. Here's how it is done in Bun: https://github.com/facebookresearch/shumai/blob/main/shumai/...
We've been using this feature heavily in Shumai.
I think you are vastly overestimating the complexity associated with this (user exposed ref-counting/garbage collection) and may not be totally up to date on what's implemented.
- Shumai: Fast Differentiable Tensor Library in TypeScript with Bun and Flashlight
- Shumai: A fast differentiable tensor library for research in TypeScript and JavaScript
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7% Speedup from Switch to and
This thought is pretty much the exact motivation behind a recent effort I’m helping out with https://github.com/facebookresearch/shumai
Memcached
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System Design: Databases and DBMS
Memcached
- Redis Re-Implemented with SQLite
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Best engineering interview question I've gotten
> Multiple clients racing can't be fixed.
Really? You can't think of a single way for multiple clients to operate on the same data without racing? (Here's a hint if you're still having trouble: https://github.com/memcached/memcached/wiki/Commands#cas.)
- Memcached 1.6.25 Release Notes
- Memcached 1.6.24 Release Notes
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How to choose the right type of database
Memcached: A simple, open-source, distributed memory object caching system primarily used for caching strings. Best suited for lightweight, non-persistent caching needs.
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Sieve is simpler than LRU
Oh, thank you! I didn't realize that LRU Maintainer Thread was more than an expiration reaper. When it was first being introduced that was its first responsibility as lazy expiration removal by size eviction meant dead entries wasted capacity. It was all work in progress when I had read about it [1] and talked to dormando, so it got fuzzy. The compat code [2, 3] might have also thrown me off if I only looked at the setting and not the usage. Its a neat variant to all of these ideas.
[1] https://github.com/memcached/memcached/pull/97
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A Developer's Journal: Simplifying the Twelve-Factor App
stores session state in a session store like Memcached or Redis.
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In-memory database Redis wants to dabble in disk
memcached has recently gained the ability to spill to disk: https://github.com/memcached/memcached/wiki/Extstore
we recently implemented this to grow our caches to >50TB
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Django Caching 101: Understanding the Basics and Beyond
Django supports using Memcached as a cache backend. Memcached is a high-performance, distributed memory caching system that can be used to store cached data across multiple servers.
What are some alternatives?
rosettaboy - A gameboy emulator in several different languages
Varnish - The project homepage
jittor - Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
node-cache - A simple in-memory cache for nodejs
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
dragonfly - A modern replacement for Redis and Memcached
devdocs - API Documentation Browser
node-cache - a node internal (in-memory) caching module
FrameworkBenchmarks - Source for the TechEmpower Framework Benchmarks project
KeyDB - A Multithreaded Fork of Redis
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Redis - Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, Streams, HyperLogLogs, Bitmaps.