Storage-Intensive Supercomputing Benchmark Study

Cohen, Joel A.; Dossa, D.; Gokhale, Maya; Hysom, David; May, John; Pearce, Roger; Yoo, Andy

doi:10.2172/924182

Cited by 7 publications

(5 citation statements)

References 5 publications

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“…As a sampling of such research, Cohen et al [9] comparatively evaluated an SSD array against local disk and a file server using three supercomputing benchmarks. Further, considering a wider range of SSD types and parallel I/O traces, [18,39] provided a broader understanding of SSD I/O performance for various scientific data-intensive workloads.…”

Section: Related Workmentioning

confidence: 99%

Exploring the Future of Out-of-Core Computing with Compute-Local Non-Volatile Memory

Wilson

Choi

Shalf

et al. 2014

Scientific Programming

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Abstract. Drawing parallels to the rise of general purpose graphical processing units (GPGPUs) as accelerators for specific high-performance computing (HPC) workloads, there is a rise in the use of non-volatile memory (NVM) as accelerators for I/O-intensive scientific applications. However, existing works have explored use of NVM within dedicated I/O nodes, which are distant from the compute nodes that actually need such acceleration. As NVM bandwidth begins to out-pace point-to-point network capacity, we argue for the need to break from the archetype of completely separated storage.Therefore, in this work we investigate co-location of NVM and compute by varying I/O interfaces, file systems, types of NVM, and both current and future SSD architectures, uncovering numerous bottlenecks implicit in these various levels in the I/O stack. We present novel hardware and software solutions, including the new Unified File System (UFS), to enable fuller utilization of the new compute-local NVM storage. Our experimental evaluation, which employs a real-world Out-of-Core (OoC) HPC application, demonstrates throughput increases in excess of an order of magnitude over current approaches.

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Section: Related Workmentioning

confidence: 99%

Exploring the Future of Out-of-Core Computing with Compute-Local Non-Volatile Memory

Wilson

Choi

Shalf

et al. 2014

Scientific Programming

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“…To evaluate the performance of QFS on ingest and query workloads we have extended the entity extraction benchmark Lextrac [13]. The benchmark stresses the novel aspects of QFS by the extensive use of links to express relationships among objects, and by the storage and retrieval of searchable metadata attached to links and files.…”

Section: User-defined Metadata: Ingest and Querymentioning

confidence: 99%

Design and Implementation of a Metadata-rich File System

Ames¹,

Gokhale²,

Maltzahn³

2010

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Despite continual improvements in the performance and reliability of large scale file systems, the management of user-defined file system metadata has changed little in the past decade. The mismatch between the size and complexity of large scale data stores and their ability to organize and query their metadata has led to a de facto standard in which raw data is stored in traditional file systems, while related, application-specific metadata is stored in relational databases. This separation of data and semantic metadata requires considerable effort to maintain consistency and can result in complex, slow, and inflexible system operation. To address these problems, we have developed the Quasar File System (QFS), a metadata-rich file system in which files, user-defined attributes, and file relationships are all first class objects. In contrast to hierarchical file systems and relational databases, QFS defines a graph data model composed of files and their relationships. QFS incorporates Quasar, an XPATH-extended query language for searching the file system. Results from our QFS prototype show the effectiveness of this approach. Compared to the de facto standard, the QFS prototype shows superior ingest performance and comparable query performance on user metadata-intensive operations and superior performance on normal file metadata operations.

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“…Specifically targeting supercomputing benchmarks, Cohen et al compared the I/O performance of a Flash SSD array against a local disk and networked storage [23]. In particular, they discovered that SSDs' performance gain with a mixed read/write graph processing benchmark is much less than the gain with read-only synthetic workloads.…”

Section: Background and Related Workmentioning

confidence: 99%

A performance evaluation of scientific I/O workloads on Flash-based SSDs

Park

Shen

2009

2009 IEEE International Conference on Cluster Computing and Workshops

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Abstract-Flash-based solid state disks (SSDs) are an alternative form of storage device that promises to deliver higher performance than the traditional mechanically rotating hard drives. While SSDs have seen utilization in embedded, consumer, and server computer systems, there has been little understanding of its performance effects with scientific I/O workloads. This paper provides a trace driven performance evaluation of scientific I/O workloads on SSDs. We find that SSDs only provide modest performance gains over mechanical hard drives due to the writeintensive nature of many scientific workloads. Other workloads (like read-mostly web servers) would likely see much larger gains. Additionally, we observe that the concurrent I/O (when multiple parallel processes simultaneously access a single storage device) may significantly affect the SSD performance. However, such effects appear to be dependent on specific SSD implementation features and they are hard to predict in a general fashion. These results suggest that abundant cautions are needed when supporting high-performance scientific I/O workloads on Flashbased SSDs.

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Storage-Intensive Supercomputing Benchmark Study

Cited by 7 publications

References 5 publications

Exploring the Future of Out-of-Core Computing with Compute-Local Non-Volatile Memory

Exploring the Future of Out-of-Core Computing with Compute-Local Non-Volatile Memory

Design and Implementation of a Metadata-rich File System

A performance evaluation of scientific I/O workloads on Flash-based SSDs

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