S3 was great for parallelism, cost, and durability, but every tool the genomics researchers used expected a local Linux filesystem. Researchers were forever copying data back and forth, managing multiple, sometimes inconsistent copies. This data friction—S3 on one side, a filesystem on the other, and a manual copy pipeline in between—is something I’ve seen over and over in the years since. In media and entertainment, in pretraining for machine learning, in silicon design, and in scientific computing. Different tools are written to access data in different ways and it sucks when the API that sits in front of our data becomes a source of friction that makes it harder to work with.
Continue reading...
。业内人士推荐搜狗输入法下载作为进阶阅读
早期太阳系有机质“快递员”如何工作？嫦娥五号和六号月壤研究揭秘
done; REPLY="$_r;";;
聚焦全球优秀创业者，项目融资率接近97%，领跑行业
Best for Big Ten games