2010
DOI: 10.1007/s10586-010-0132-9
|View full text |Cite
|
Sign up to set email alerts
|

Middleware support for many-task computing

Abstract: While the I/O functions described in the MPI standard included shared file pointer support from the beginning, the performance and portability of these functions have been subpar at best. ROMIO [1], which provides the MPI-IO functionality for most MPI libraries, to this day uses a separate file to manage the shared file pointer. This file provides the shared location that holds the current value of the shared file pointer. Unfortunately, each access to the shared file pointer involves file lock management and … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
17
0
1

Year Published

2011
2011
2020
2020

Publication Types

Select...
4
3
2

Relationship

4
5

Authors

Journals

citations
Cited by 38 publications
(18 citation statements)
references
References 38 publications
0
17
0
1
Order By: Relevance
“…FusionFS has already scaled to 1K nodes, and we aim to scale up FusionFS+HyCache to 10K nodes. We will also apply HyCache to Many-Task Computing (MTC) [31][32][33][34], which has specific emphasis on data-intensive computing [35] and cloud computing [36].…”
Section: Discussionmentioning
confidence: 99%
“…FusionFS has already scaled to 1K nodes, and we aim to scale up FusionFS+HyCache to 10K nodes. We will also apply HyCache to Many-Task Computing (MTC) [31][32][33][34], which has specific emphasis on data-intensive computing [35] and cloud computing [36].…”
Section: Discussionmentioning
confidence: 99%
“…FusionFS is optimized for a subset of HPC and many-task computing (MTC) [12,59,62,63] workloads, and it is designed for extreme scales [61]. These workloads are often extremely data-intensive [56,58,60], and optimizing data locality [55] becomes critical to achieving good scalability and performance.…”
Section: A Fusionfs: Distributed Metadata Managementmentioning
confidence: 99%
“…We investigated the largest available trace of real MTC workloads, collected over a 17-month period comprising of 173M tasks [38] [39]. We filtered out the logs to isolate only the 160K-core IBM Blue Gene/P Intrepid supercomputer from Argonne National Laboratory, which netted about 34.8M tasks with the minimum runtime of 0 seconds, maximum runtime of 1469.62 seconds, average runtime of 95.20 seconds, and standard deviation of 188.08.…”
Section: A Workload Tracementioning
confidence: 99%