Using MPI: portable parallel programming with the message-passing interface
Using MPI: portable parallel programming with the message-passing interface
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
A network-failure-tolerant message-passing system for terascale clusters
ICS '02 Proceedings of the 16th international conference on Supercomputing
A Cluster Operating System Supporting Parallel Computing
Cluster Computing
STORM: lightning-fast resource management
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
A network-failure-tolerant message-passing system for terascale clusters
International Journal of Parallel Programming
Current Practice and a Direction Forward in Checkpoint/Restart Implementations for Fault Tolerance
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 18 - Volume 19
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Right-weight kernels: an off-the-shelf alternative to custom light-weight kernels
ACM SIGOPS Operating Systems Review
How to build a fast and reliable 1024 node cluster with only one disk
The Journal of Supercomputing
STORM: Scalable Resource Management for Large-Scale Parallel Computers
IEEE Transactions on Computers
Middleware in Modern High Performance Computing System Architectures
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part II
Complementarity between Virtualization and Single System Image Technologies
Euro-Par 2008 Workshops - Parallel Processing
TakTuk, adaptive deployment of remote executions
Proceedings of the 18th ACM international symposium on High performance distributed computing
Remote Process Execution and Remote File I/O for Heterogeneous Processors in Cluster Systems
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Kittyhawk: enabling cooperation and competition in a global, shared computational system
IBM Journal of Research and Development
Impact of sub-optimal checkpoint intervals on application efficiency in computational clusters
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
EURO-PDP'00 Proceedings of the 8th Euromicro conference on Parallel and distributed processing
FINAL: flexible and scalable composition of file system name spaces
Proceedings of the 1st International Workshop on Runtime and Operating Systems for Supercomputers
Fast and scalable startup of MPI programs in infiniband clusters
HiPC'04 Proceedings of the 11th international conference on High Performance Computing
Application monitoring and checkpointing in HPC: looking towards exascale systems
Proceedings of the 50th Annual Southeast Regional Conference
A design of hybrid operating system for a parallel computer with multi-core and many-core processors
Proceedings of the 2nd International Workshop on Runtime and Operating Systems for Supercomputers
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The Beowulf Distributed Process Space (BProc) is a set of Linux kernel modifications which provides a single system image and process migration facilities for processes running in a Beowulf style cluster. With BProc, all the processes running in a cluster are visible on the cluster front end machine and are controllable via existing UNIX process control mechanisms. Process creation is done on the front end machine and the processes are placed on the nodes where they will run with BProc's process migration mechanism.These two features combined greatly simplify creating and cleaning up parallel jobs as well as removing the necessity of a user login to remote nodes in the cluster. Removing the need for user logins drastically reduces the mount of software required on cluster nodes.Job startup with BProc's process migration mechanism is faster than the traditional method of logging into a node and starting the process with rsh. BProc does not affect file or network I/O of processes running on remote nodes so the vast majority of MPI applications will experience no performance loss as a result of being managed by BProc.