下图是上面这个案例所对应的拓扑图:
文章插图
总结概要对于从元素运算到矩阵运算再到张量运算,最后抽象到图运算 , 这个预算模式的发展历程,在每个阶段都需要有配套的工具来进行支持 。比如矩阵时代的numpy,张量时代的mindspore,还有图时代的mindspore-gl 。我们未必说哪种运算模式就一定更加先进,但是对于coder来说,“公式即代码”这是一个永恒的话题,而mindspore-gl在这一个工作上确实做的很好 。不仅仅是图模式的编程可读性更高,在GPU运算的性能上也有非常大的优化 。
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作者ID:DechinPhy
更多原著文章请参考:https://www.cnblogs.com/dechinphy/
打赏专用链接:https://www.cnblogs.com/dechinphy/gallery/image/379634.html
腾讯云专栏同步:https://cloud.tencent.com/developer/column/91958
CSDN同步链接:https://blog.csdn.net/baidu_37157624?spm=1008.2028.3001.5343
51CTO同步链接:https://blog.51cto.com/u_15561675
参考链接
- https://gitee.com/mindspore/graphlearning
- https://www.bilibili.com/video/BV14a411976w/
- Seastar: Vertex-Centric Progamming for Graph Neural Networks. Yidi Wu and other co-authors.
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