Dr. Xuchao Xie Profile

Dr. Xuchao Xie

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Proceedings Article | 11 July 2024 Paper

GABB: the plan-based job scheduling optimized by genetic algorithm for HPC systems with shared burst buffers

Shuaizhe Lv, Xuchao Xie, Zhenlong Song

Proceedings Volume 13210, 132101Y (2024) https://doi.org/10.1117/12.3034965

KEYWORDS: Computing systems, Genetic algorithms, Data storage, Mathematical optimization, Computer simulations, Systems modeling, Genetics, Computer architecture, Parallel computing

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Burst Buffer was proposed to address the growing performance gap between computation and I/O in high-performance computing systems (HPC). However, the introduction of Burst Buffer has brought new issues in system resource management and job scheduling. Resource management systems on HPC platforms lack efficient management of multiple types of resources, and the allocation of computing resources and Burst Buffer resources is independent of each other. This can lead to underutilization of system resources and job blocking. To address these issues, this paper proposes GABB, a plan-based job scheduling strategy for shared Burst Buffer, and utilizes genetic algorithms for optimization. GABB employs a plan-based job scheduling strategy to uniformly schedule all jobs in the waiting queue to generate an execution plan. Furthermore, GABB comprehensively considers changes in system resources and the job's demand for computing and Burst Buffer resources during the job scheduling process. Finally, GABB utilizes an improved genetic algorithm to optimize the job scheduling scheme. We conducted experimental simulations of a shared Burst Buffer system and implemented a plan-based job scheduling algorithm. The experimental results indicate that BBGA significantly reduces the mean waiting time of jobs by over 20% compared to the Shortest Job First (SJF) algorithm, and reduces the mean bounded slowdown of jobs by over 25%.

Proceedings Article | 18 February 2022 Paper

Load-aware transmission mechanism for NVMeoF storage networks

Xinghan Qiao, Xuchao Xie, Liquan Xiao

Proceedings Volume 12162, 121620H (2022) https://doi.org/10.1117/12.2628060

KEYWORDS: Data centers, Data storage, Computing systems, Prototyping

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NVMe over TCP is a key technology for building large-scale high-performance storage systems. It can realize NVMeoF (NVMe over Fabrics) storage network based on existing data center network infrastructure and standard TCP/IP software protocol stack. In this paper, we design and implement the Load-aware NVMeoF message processing mechanism LANoT (Load-aware NVMe over TCP). Firstly, the interrupt coalescing technology based on PDU aggregation is used to alleviate the interrupt storm problem and achieve high throughput. Secondly, matching the special message processing mechanism, which can effectively improve the key performance indicators according to the I/O characteristics of different dedicated queues. This paper implements the LANoT prototype system in Linux kernel. The performance test results show that comparing to NVMe over TCP implementation in standard Linux kernel, LANoT can significantly improve IOPS metrics and reduce CPU resource consumption by more than 50%.

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