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    Maximizing I/O Bandwidth for Out-of-Core HPC Applications on Homogeneous and Heterogeneous Large-Scale Systems

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    Alturkestani_Tariq_Dissertation_Sept27.pdf
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    Type
    Dissertation
    Authors
    Alturkestani, Tariq cc
    Advisors
    Keyes, David E. cc
    Committee members
    Shihada, Basem cc
    Moshkov, Mikhail cc
    Sun, Xian-He
    Program
    Computer Science
    KAUST Department
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Date
    2020-09-30
    Embargo End Date
    2021-10-01
    Permanent link to this record
    http://hdl.handle.net/10754/665396
    
    Metadata
    Show full item record
    Access Restrictions
    At the time of archiving, the student author of this dissertation opted to temporarily restrict access to it. The full text of this dissertation will become available to the public after the expiration of the embargo on 2021-10-01.
    Abstract
    Out-of-Core simulation systems often produce a massive amount of data that cannot t on the aggregate fast memory of the compute nodes, and they also require to read back these data for computation. As a result, I/O data movement can be a bottleneck in large-scale simulations. Advances in memory architecture have made it feasible and a ordable to integrate hierarchical storage media on large-scale systems, starting from the traditional Parallel File Systems (PFSs) to intermediate fast disk technologies (e.g., node-local and remote-shared NVMe and SSD-based Burst Bu ers) and up to CPU main memory and GPU High Bandwidth Memory (HBM). However, while adding additional and faster storage media increases I/O bandwidth, it pressures the CPU, as it becomes responsible for managing and moving data between these layers of storage. Simulation systems are thus vulnerable to being blocked by I/O operations. The Multilayer Bu er System (MLBS) proposed in this research demonstrates a general and versatile method for overlapping I/O with computation that helps to ameliorate the strain on the processors through asynchronous access. The main idea consists in decoupling I/O operations from computational phases using dedicated hardware resources to perform expensive context switches. MLBS monitors I/O tra c in each storage layer allowing fair utilization of shared resources. By continually prefetching up and down across all hardware layers of the memory and storage subsystems, MLBS transforms the original I/O-bound behavior of evaluated applications and shifts it closer to a memory-bound or compute-bound regime. The evaluation on the Cray XC40 Shaheen-2 supercomputer for a representative I/Obound application, seismic inversion, shows that MLBS outperforms state-of-the-art PFSs, i.e., Lustre, Data Elevator and DataWarp by 6.06X, 2.23X, and 1.90X, respectively. On the IBM-built Summit supercomputer, using 2048 compute nodes equipped with a total of 12288 GPUs, MLBS achieves up to 1.4X performance speedup compared to the reference PFS-based implementation. MLBS is also demonstrated on applications from cosmology, combustion, and a classic out-of-core computational physics and linear algebra routines.
    Citation
    Alturkestani, T. (2020). Maximizing I/O Bandwidth for Out-of-Core HPC Applications on Homogeneous and Heterogeneous Large-Scale Systems. KAUST Research Repository. https://doi.org/10.25781/KAUST-L1536
    DOI
    10.25781/KAUST-L1536
    ae974a485f413a2113503eed53cd6c53
    10.25781/KAUST-L1536
    Scopus Count
    Collections
    PhD Dissertations; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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