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

[Performance] cuTN circuit2einsum slower than opt_einsum

未关闭
#90 5 条评论 0 个 reaction 已指派 2 人 在 GitHub 查看

@haidarazzam 已经在做这个了。

开始于 2023年9月26日。

评估

这个 Issue 还没有评估数据。

描述

bug invalid triage
Discussed in https://github.com/NVIDIA/cuQuantum/discussions/53

Originally posted by rht May 12, 2023
I was benchmarking cuTensorNet and opt_einsum on the QFT and QAOA circuit, and I found the former to be consistently slower than the latter.
I used the same code in https://github.com/NVIDIA/cuQuantum/discussions/23 for cuTensorNet, and for opt_einsum:

bitstring = "0" * len(qubits)
# https://optimized-einsum.readthedocs.io/en/stable/autosummary/opt_einsum.contract_path.html#opt_einsum.contract_path
expression, operands = myconverter.amplitude(bitstring=bitstring)
tic = time.time()
path, path_info = oe.contract_path(expression, *operands)
elapsed1 = time.time() - tic
print("Elapsed opt_einsum path finding", elapsed1)
tic = time.time()
output = oe.contract(expression, *operands, optimize=path)
elapsed2 = time.time() - tic
print("Elapsed opt_einsum contract", elapsed2)

Plot for QFT:
benchmark

I think it has something to do with cuTensorNet's path finding being closer to the global optimum. Is there a way to tweak the hyperoptimizer to either stop early, or to have a larger error tolerance, so as to minimize the overall time?

主要语言
Jupyter Notebook
星标
502
派生
102
PR 合并指标
30 天内没有已合并 PR

环境准备

  • 没有 Dockerfile 或 Docker Compose 文件
  • 没有 Pull Request 模板
  • 阅读贡献指南

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/cuQuantum 的其他 Issue

查看 NVIDIA/cuQuantum 的全部 Issue

把新 issue 发到你的邮箱

精选适合新手参与的 GitHub issue 摘要。