Hacktoberfest 2026:维护者为十月标记出来的 issue,仍然开放、适合新手。 浏览 Hacktoberfest issue

Size computation slows bulk insert significantly

未关闭
#237 1 条评论 0 个 reaction 已指派 0 人 在 GitHub 查看

维护者通常 2 天内回复

还没有人认领这个 Issue。

评估

难度
5/5
预计耗时
一周以上
新手友好度
35/100
Issue 类型
缺陷
描述清晰度
基本清楚
活跃度
停滞
技术栈
cpp
领域
performance

调研方向

从 include/cuco/detail/static_map.inl 的第149-151行开始,对批量插入进行性能分析,以确认 device-to-host memcpy 和同步的开销。比较计算或避免维护大小的替代方案,然后验证 bulk insert 不再产生报告中的每操作开销,同时不破坏与大小相关的行为。

由索引模型根据 Issue 内容生成。

描述

P1: Should have type: feature request

The size computation requires a small memcpy from device to host and then a synchronization. Each one is the cause of serious performance degradation.

https://github.com/NVIDIA/cuCollections/blob/8786234a38a4d1283c6dc2011e45d14801510725/include/cuco/detail/static_map.inl#L149-L151

The synchronization is bad because it means that other unrelated streams are unable to do work.

The memcpy is bad because future copies are queued behind this one in architectures that have a limited number of cuda copy engines.

I was able to get a significant performance improvement by deleting these lines.

There ought to be a better way to compute size. Perhaps a lazy method. If this is too difficult, you might consider using templates to allow the user to choose to not maintain size_ at all! Use templates to change the type of size_ from int to a struct that has no members. That way it doesn't take up any space. Provide no methods on this struct so that the size_ doesn't get accidentally used. It will still use some space on the host but that seems like no big deal.

https://github.com/NVIDIA/cuCollections/issues/237#tasklist-block-efc3d0dd-74a4-4f46-b10e-d6fde965d057

主要语言
Cuda
星标
671
派生
122
平均合并
4 天 19 小时
30 天内合并 PR
10

环境准备

在 Codespaces 中打开

在浏览器里用你自己的 GitHub 账号启动这个项目的开发容器。

从这里开始

  1. 先读完整个 Issue,再读项目的贡献指南。
  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库,在一个分支上完成修改。
  4. 提交 Pull Request,并在描述里引用这个 Issue 编号。

NVIDIA/cuCollections 的其他 Issue

查看 NVIDIA/cuCollections 的全部 Issue

相似的 Issue

更多 Performance Issue

把新 issue 发到你的邮箱

精选适合新手参与的 GitHub issue 摘要。