Speed up your code like crazy!
Maxwell is a new kind of AI. It's a code execution model that speeds up your code on CPUs and GPUs.
"Code execution models" are a new category of AI. Maxwell is the first one, but this category will explode in popularity, and you'll see why.
Say you have a script that moves and processes some data.
You integrate your code with Maxwell, run it, and let it observe how it runs on your hardware and analyze the data your script moves around.
Maxwell will identify bottlenecks and look for faster algorithms and machine instructions for your workload. As long as your script runs, Maxwell rewrites the binary to make it faster.
In one example, Maxwell made a pandas pipeline 38.4x faster. It used more CPU cores, combined processing steps, reduced unnecessary memory reads and writes, and selected the right algorithms for the data the script was processing.
For example, imagine you want to check whether a number belongs to a collection. You could use hashing, but if the numbers occupy a small, dense range, a compact bitmap can make that check much faster.
In short, that's one of the algorithmic data-dependent tricks Maxwell can leverage to speed things up.
Here is the most impressive part of all of this:
Maxwell produces a machine-checked mathematical proof that each replacement preserves the original behavior.
Basically, any code they modify will always produce the same output as the old one.
This is really cool for anyone working on AI or data engineering workflows. You will squeeze much more work from the hardware without rewriting your application.
You can try out your scripts using Maxwell by going to this link: fandf.co/4iugTRP
Thanks to the @_doubleAI_ team for partnering with me on this post.
像疯了一样加速你的代码！
Maxwell 是一种新型 AI。它是一个代码执行模型，能在 CPU 和 GPU 上加速你的代码。
"代码执行模型"是 AI 的一个新类别。Maxwell 是第一个，但这个类别会迅速爆火，你会明白为什么的。
假设你有一个移动和处理数据的脚本。
你将代码与 Maxwell 集成，运行它，让它观察在你的硬件上如何运行，并分析你的脚本移动的数据。
Maxwell 会识别瓶颈，并为你的工作负载寻找更快的算法和机器指令。只要你的脚本在运行，Maxwell 就会重写二进制文件让它更快。
在一个例子中，Maxwell 让一个 pandas 流水线快了 38.4 倍。它使用了更多 CPU 核心，合并了处理步骤，减少了不必要的内存读写，并为脚本处理的数据选择了合适的算法。
例如，假设你想检查一个数字是否属于某个集合。你可以用哈希，但如果数字占据一个小的密集范围，紧凑位图可以让这个检查快得多。
简而言之，这就是 Maxwell 可以利用的算法数据相关技巧之一，用来加速。
以下是这一切中最令人印象深刻的部分：
Maxwell 会生成机器检查的数学证明，证明每次替换都保留了原始行为。
基本上，他们修改的任何代码都会与旧代码产生完全相同的输出。
这对任何从事 AI 或数据工程工作流的人来说都非常酷。无需重写应用，你就能从硬件中榨取更多算力。
你可以通过这个链接试用 Maxwell 运行你的脚本：fandf.co/4iugTRP
感谢 @_doubleAI_ 团队与我合作发布这篇帖子。