Title : 
Investigation of leading HPC I/O performance using a scientific-application derived benchmark
         
        
            Author : 
Borrill, Julian ; Oliker, Leonid ; Shalf, John ; Shan, Hongzhang
         
        
            Author_Institution : 
Lawrence Berkeley National Laboratory, Berkeley, CA
         
        
        
        
        
        
            Abstract : 
With the exponential growth of high-fidelity sensor and simulated data, the scientific community is increasingly reliant on ultrascale HPC resources to handle their data analysis requirements. However, to utilize such extreme computing power effectively, the I/O components must be designed in a balanced fashion, as any architectural bottleneck will quickly render the platform intolerably inefficient. To understand I/O performance of data-intensive applications in realistic computational settings, we develop a lightweight, portable benchmark called MADbench2, which is derived directly from a large-scale Cosmic Microwave Background (CMB) data analysis package. Our study represents one of the most comprehensive I/O analyses of modern parallel filesystems, examining a broad range of system architectures and configurations, including Lustre on the Cray XT3 and Intel Itanium2 cluster; GPFS on IBM Power5 and AMD Opteron platforms; two BlueGene/L installations utilizing GPFS and PVFS2 filesystems; and CXFS on the SGI Altix3700. We present extensive synchronous I/O performance data comparing a number of key parameters including concurrency, POSIX- versus MPI-IO, and unique- versus shared-file accesses, using both the default environment as well as highly-tuned I/O parameters. Finally, we explore the potential of asynchronous I/O and quantify the volume of computation required to hide a given volume of I/O. Overall our study quantifies the vast differences in performance and functionality of parallel filesystems across state-of-the-art platforms, while providing system designers and computational scientists a lightweight tool for conducting further analyses.
         
        
            Keywords : 
Analytical models; Computational modeling; Computer applications; Computer architecture; Concurrent computing; Data analysis; Large-scale systems; Packaging; Performance analysis; Portable computers;
         
        
        
        
            Conference_Titel : 
Supercomputing, 2007. SC '07. Proceedings of the 2007 ACM/IEEE Conference on
         
        
            Conference_Location : 
Reno, NV, USA
         
        
            Print_ISBN : 
978-1-59593-764-3
         
        
            Electronic_ISBN : 
978-1-59593-764-3
         
        
        
            DOI : 
10.1145/1362622.1362636