ACM Transactions on Programming Languages and Systems (TOPLAS)
A survey of process migration mechanisms
ACM SIGOPS Operating Systems Review
Process-originated migration in a heterogeneous environment
CSC '89 Proceedings of the 17th conference on ACM Annual Computer Science Conference
Journal of Parallel and Distributed Computing - Special issue on heterogeneous processing
A unified model of pointwise equivalence of procedural computations
ACM Transactions on Programming Languages and Systems (TOPLAS)
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
Object and native code thread mobility among heterogeneous computers (includes sources)
SOSP '95 Proceedings of the fifteenth ACM symposium on Operating systems principles
Efficient and flexible fault tolerance and migration of scientific simulations using CUMULVS
SPDT '98 Proceedings of the SIGMETRICS symposium on Parallel and distributed tools
The Architecture of the Ara Platform for Mobile Agents
MA '97 Proceedings of the First International Workshop on Mobile Agents
Sumatra: A Language for Resource-Aware Mobile Programs
MOS '96 Selected Presentations and Invited Papers Second International Workshop on Mobile Object Systems - Towards the Programmable Internet
HPDC '96 Proceedings of the 5th IEEE International Symposium on High Performance Distributed Computing
A Task Migration Implementation of the Message-Passing Interface
HPDC '96 Proceedings of the 5th IEEE International Symposium on High Performance Distributed Computing
Dome: Distributed Object Migration Environment
Dome: Distributed Object Migration Environment
Heterogeneous Process Migration: The Tui System
Heterogeneous Process Migration: The Tui System
Process state capture and recovery in high-performance heterogeneous distributed computing systems
Process state capture and recovery in high-performance heterogeneous distributed computing systems
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Type-Assisted Dynamic Buffer Overflow Detection
Proceedings of the 11th USENIX Security Symposium
Mobile MPI programs in computational grids
Proceedings of the eleventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Recent advances in checkpoint/recovery systems
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Execution migration in a heterogeneous-ISA chip multiprocessor
ASPLOS XVII Proceedings of the seventeenth international conference on Architectural Support for Programming Languages and Operating Systems
Hi-index | 0.00 |
The ability to capture the state of a process and later recover that state in the form of an equivalent running process is the basis for a number of important features in parallel and distributed systems. Adaptive load sharing and fault tolerance are well‐known examples. Traditional state capture mechanisms have employed an external agent (such as the operating system kernel) to examine and capture process state. However, the increasing prevalence of heterogeneous cluster and “metacomputing” systems as high‐performance computing platforms has prompted investigation of process‐internal state capture mechanisms. Perhaps the greatest advantage of the process‐internal approach is the ability to support cross‐platform state capture and recovery, an important feature in heterogeneous environments. Among the perceived disadvantages of existing process‐internal mechanisms are poor performance in multiple respects, and difficulty of use in terms of programmer effort. In this paper we describe a new process‐internal state capture and recovery mechanism: Process Introspection. Experiences with this system indicate that the perceived disadvantages associated with process‐internal mechanisms can be largely overcome, making this approach to state capture an appropriate one for cluster and metacomputing environments.