zstd
Bullet
zstd | Bullet | |
---|---|---|
109 | 41 | |
22,523 | 11,998 | |
1.9% | 1.7% | |
9.7 | 4.5 | |
6 days ago | 14 days ago | |
C | C++ | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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zstd
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Rethinking string encoding: a 37.5% space efficient encoding than UTF-8 in Fury
> In such cases, the serialized binary are mostly in 200~1000 bytes. Not big enough for zstd to work
You're not referring to the same dictionary that I am. Look at --train in [1].
If you have a training corpus of representative data, you can generate a dictionary that you preshare on both sides which will perform much better for very small binaries (including 200-1k bytes).
If you want maximum flexibility (i.e. you don't know the universe of representative messages ahead of time or you want maximum compression performance), you can gather this corpus transparently as messages are generated & then generate a dictionary & attach it as sideband metadata to a message. You'll probably need to defer the decoding if it references a dictionary not yet received (i.e. send delivers messages out-of-order from generation). There are other techniques you can apply, but the general rule is that your custom encoding scheme is unlikely to outperform zstd + a representative training corpus. If it does, you'd need to actually show this rather than try to argue from first principles.
[1] https://github.com/facebook/zstd/blob/dev/programs/zstd.1.md
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Drink Me: (Ab)Using a LLM to Compress Text
> Doesn't take large amount of GPU resources
This is an understatement, zstd dictionary compression and decompression are blazingly fast: https://github.com/facebook/zstd/blob/dev/README.md#the-case...
My real-world use case for this was JSON files in a particular schema, and the results were fantastic.
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SQLite VFS for ZSTD seekable format
This VFS will read a sqlite file after it has been compressed using [zstd seekable format](https://github.com/facebook/zstd/blob/dev/contrib/seekable_f...). Built to support read-only databases for full-text search. Benchmarks are provided in README.
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Chrome Feature: ZSTD Content-Encoding
Of course, you may get different results with another dataset.
gzip (zlib -6) [ratio=32%] [compr=35Mo/s] [dec=407Mo/s]
zstd (zstd -2) [ratio=32%] [compr=356Mo/s] [dec=1067Mo/s]
NB1: The default for zstd is -3, but the table only had -2. The difference is probably small. The range is 1-22 for zstd and 1-9 for gzip.
NB2: The default program for gzip (at least with Debian) is the executable from zlib. With my workflows, libdeflate-gzip iscompatible and noticably faster.
NB3: This benchmark is 2 years old. The latest releases of zstd are much better, see https://github.com/facebook/zstd/releases
For a high compression, according to this benchmark xz can do slightly better, if you're willing to pay a 10× penalty on decompression.
xz -9 [ratio=23%] [compr=2.6Mo/s] [dec=88Mo/s]
zstd -9 [ratio=23%] [compr=2.6Mo/s] [dec=88Mo/s]
- Zstandard v1.5.6 – Chrome Edition
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Optimizating Rabin-Karp Hashing
Compression, synchronization and backup systems often use rolling hash to implement "content-defined chunking", an effective form of deduplication.
In optimized implementations, Rabin-Karp is likely to be the bottleneck. See for instance https://github.com/facebook/zstd/pull/2483 which replaces a Rabin-Karp variant by a >2x faster Gear-Hashing.
- Show HN: macOS-cross-compiler – Compile binaries for macOS on Linux
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Cyberpunk 2077 dev release
Get the data https://publicdistst.blob.core.windows.net/data/root.tar.zst magnet:?xt=urn:btih:84931cd80409ba6331f2fcfbe64ba64d4381aec5&dn=root.tar.zst How to extract https://github.com/facebook/zstd Linux (debian): `sudo apt install zstd` ``` tar -I 'zstd -d -T0' -xvf root.tar.zst ```
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Honey, I shrunk the NPM package · Jamie Magee
I've done that experiment with zstd before.
https://github.com/facebook/zstd/blob/dev/programs/zstd.1.md...
Not sure about brotli though.
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How in the world should we unpack archive.org zst files on Windows?
If you want this functionality in zstd itself, check this out: https://github.com/facebook/zstd/pull/2349
Bullet
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Blaze: A High Performance C++ Math library
For typical game physics engines... not that much. Math libraries like Eigen or Blaze use lots of template metaprogramming techniques under the hood that can help when you're doing large batched matrix multiplications (since it can remove temporary allocations at compile-time and can also fuse operations efficiently, as well as applying various SIMD optimizations), but it doesn't really help when you need lots of small operations (with mat3 / mat4 / vec3 / quat / etc.). Typical game physics engines tend to use iterative algorithms for their solvers (Gauss-Seidel, PBD, etc...) instead of batched "matrix"-oriented ones, so you'll get less benefits out of Eigen / Blaze compared to what you typically see in deep learning / scientific computing workloads.
The codebases I've seen in many game physics engines seem to all roll their own math libraries for these stuff, or even just use SIMD (SSE / AVX) intrinsics directly. Examples: PhysX (https://github.com/NVIDIA-Omniverse/PhysX), Box2D (https://github.com/erincatto/box2d), Bullet (https://github.com/bulletphysics/bullet3)...
- Looking for specific pre-Microsoft Havok Physics SDK version (2013, 2014)
- Software for Mechanism Analysis
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Does anyone know any good open source project to optimize?
I suspect most C++ physics libraries like Box2D (https://github.com/erincatto/box2d) or Bullet3 (https://github.com/bulletphysics/bullet3) could really benefit a lot from SIMD.
- After months of work, I'm excited to share the first release of Godot Jolt, an extension that integrates the Jolt physics engine into Godot, demonstrated using GDQuest's RoboBlast
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X4's Upcoming Multiplayer Features Are a Huge Step Forward
No, they replaced Bullet with Jolt. That is considerably more than "some adjustment", regardless of what you think of the result.
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Brick Breaker
Vulkan graphics via Intel GVK, and physics via Bullet
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Ive been programming for four years and I told my dad to watch long videos and complete your own projects to learn most efficiently. He thinks he’s ready to tackle any project after a ten minute video…
The first two have a bunch of great examples, and I’m tying them together by refactoring some of the THREE examples to fit the ECS paradigm defined in AFrame. then upping the ante by adding physics using AMMO, which is more challenging since it’s only a partial implementation of Bullet, and already poorly documented (yet popular) physics engine.
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Their music is just too good
Plus, SM uses a system called bullet physics, I imagine this would be rather complex to rework into a modern engine such as Unreal or Unity (after all, the majority of performance issues come from the physics engine rather than the graphics engine)
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Is anyone working on more effecient HDT-SMP?
The physics in HDT-SMP are actually being calculated outside of Skyrim's engine with Bullet, an open-source physics engine. So this isn't some limitation of Skyrim's engine.
What are some alternatives?
LZ4 - Extremely Fast Compression algorithm
PhysX - NVIDIA PhysX SDK
Snappy - A fast compressor/decompressor
Box2D - Box2D is a 2D physics engine for games
LZMA - (Unofficial) Git mirror of LZMA SDK releases
CHRONO - High-performance C++ library for multiphysics and multibody dynamics simulations
7-Zip-zstd - 7-Zip with support for Brotli, Fast-LZMA2, Lizard, LZ4, LZ5 and Zstandard
Newton Dynamics - Newton Dynamics is an integrated solution for real time simulation of physics environments.
ZLib - A massively spiffy yet delicately unobtrusive compression library.
ODE
brotli - Brotli compression format
mujoco - Multi-Joint dynamics with Contact. A general purpose physics simulator.