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Open nowPosted 102 days ago

2027校招-数学库算法开发工程师（稠密矩阵方向）-北京/上海

smartlogictech/xiaozhao44 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now2027校招-数学库算法开发工程师（稠密矩阵方向）-北京/上海smartlogictech/xiaozhao · Beijing, Chinese Mainland

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11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 102 days ago

The posting

1.算法设计与原型验证：在 CPU/GPU 异构分布式环境下，设计并实现分布式稠密线性代数算法，从数学原理和边界处理上确保算法的绝对正确。 2.硬件抽象层设计：设计统一的底层抽象接口，将分布式调度与内存管理逻辑，同具体的底层计算内核及硬件 API（如 CUDA、MKL 等）完全解耦，确保上层调度代码的硬件无关性。 3.流水线与调度设计：开发基于任务依赖图的异步调度器，设计计算与通信的掩盖（Overlap）策略，解决宏观架构上的数据依赖与任务调度问题。 4.分布式性能剖析：使用 Nsight Systems 等工具分析分布式计算与通信的瓶颈，评估不同网络拓扑下的理论通信开销，持续优化流水线。

1.数学与算法功底：对数值代数有扎实的理论直觉，能够理解并推导矩阵运算中的数学边界与收敛性问题。 标准接口与语义：深入理解 BLAS/LAPACK/cuBLAS/cuSolver 的标准语义（如数据布局、控制参数、错误处理机制等），了解矩阵分块算法的基本原理。 2.分布式计算原理：深入理解分布式计算与并发编程原理，对点对点与集合通信（Collective Communication）有清晰的认识，能够排查分布式环境下的死锁、数据竞争等典型问题。 3.优秀的编码风格与工程素养： - 追求内存的确定性：对隐式内存分配保持警惕，倾向于设计“零隐式开销”、内存生命周期清晰受控的算法接口。 - 追求控制流的简洁：具备跨架构（CPU/GPU）高性能编程直觉，注重数据局部性与控制流扁平化。 - 严谨的正确性验证与测试习惯：习惯编写完备的单元测试，能够针对数值边界（如 NaN、Inf、realmin/realmax等）设计测试用例，确保代码在异常输入下依然行为安全、可预测；熟练运用前向/后向误差分析方法，设计基于残差（Residual）与数值稳定性指标的自动化验证与回归测试体系。 4.工具与性能分析：熟练使用 Git，并能够使用 Nsight Systems 等性能剖析工具定位分布式流水线中的性能瓶颈。

【加分项】 系统阅读过《Matrix Computations》（矩阵计算）等数值线性代数经典著作。 熟悉 ScaLAPACK 风格的分布式计算逻辑与数据分布格式。 深入研究过开源分布式 HPC 核心库（如 SLATE, DPLASMA, MAGMA, ScaLAPACK 等）的源码与架构。

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