Gucci grip

@MisakaTian 用 mamba 啊

https://www.bilibili.com/video/BV1TK4y1L7DU

Java 实测

Spark

Google Colab - 2 Intel(R) Xeon(R) CPU @ 2.20GHz

Dotted two 4096x4096 matrices in 4.16 s.
Dotted two vectors of length 524288 in 0.25 ms.
SVD of a 2048x1024 matrix in 1.49 s.
Cholesky decomposition of a 2048x2048 matrix in 0.23 s.
Eigendecomposition of a 2048x2048 matrix in 13.11 s.

@IgniteWhite 太超前啦😂确实是个好东西

@pb941129 烤鸡仨小时啊 我能在冰箱里测么😂 没风扇怕烤糊了

@Aspector air 的 m1 限制在 10 瓦😂

分享一下朋友的 16inch 2.6 GHz 6-Core Intel Core i7

Dotted two 4096x4096 matrices in 0.49 s.
Dotted two vectors of length 524288 in 0.05 ms.
SVD of a 2048x1024 matrix in 0.32 s.
Cholesky decomposition of a 2048x2048 matrix in 0.07 s.
Eigendecomposition of a 2048x2048 matrix in 3.16 s.

@changepc90 这应该就是指令集差异造成的叭

@pb941129 不错还是 i9 强😂 是不是跑的时候 8 核 16 线程都占满了

@pb941129
@NoobX
@Goldilocks
@felixcode



找到了个 numpy 性能脚本 跑了一下 https://gist.github.com/markus-beuckelmann/8bc25531b11158431a5b09a45abd6276

```
Dotted two 4096x4096 matrices in 0.53 s.
Dotted two vectors of length 524288 in 0.25 ms.
SVD of a 2048x1024 matrix in 0.59 s.
Cholesky decomposition of a 2048x2048 matrix in 0.08 s.
Eigendecomposition of a 2048x2048 matrix in 4.74 s.

This was obtained using the following Numpy configuration:
blas_info:
libraries = ['cblas', 'blas', 'cblas', 'blas']
library_dirs = ['/Users/yux/miniforge3/envs/maths/lib']
include_dirs = ['/Users/yux/miniforge3/envs/maths/include']
language = c
define_macros = [('HAVE_CBLAS', None)]
blas_opt_info:
define_macros = [('NO_ATLAS_INFO', 1), ('HAVE_CBLAS', None)]
libraries = ['cblas', 'blas', 'cblas', 'blas']
library_dirs = ['/Users/yux/miniforge3/envs/maths/lib']
include_dirs = ['/Users/yux/miniforge3/envs/maths/include']
language = c
lapack_info:
libraries = ['lapack', 'blas', 'lapack', 'blas']
library_dirs = ['/Users/yux/miniforge3/envs/maths/lib']
language = f77
lapack_opt_info:
libraries = ['lapack', 'blas', 'lapack', 'blas', 'cblas', 'blas', 'cblas', 'blas']
library_dirs = ['/Users/yux/miniforge3/envs/maths/lib']
language = c
define_macros = [('NO_ATLAS_INFO', 1), ('HAVE_CBLAS', None)]
include_dirs = ['/Users/yux/miniforge3/envs/maths/include']
`
```




p.s. python 版本 3.9.1 -arm64 跑的时候关掉了所有后台

@love 有 8G 版本

@hwdef 树莓派吧 便宜又好用 性能不够就集群

你要干啥用啊 树莓派的 cpu 也挺强的 半年前做一些数值计算 树莓派 4 核心一起上并行计算比我的 macbook i9 开 4 线程计算还要快不少

@YUX 而且都 mba 了谁还要 codespace 写😂

codespace 最好的一点就是 iPad pro 配 Magic keyboard 写代码

不过最近换了 MacBook air 感觉 air 更轻一点😂

@0bit codespace 早就开始了

airbra
https://i.imgur.com/ESsvM53.jpg