Toward Performance-Driven System Support for Distributed Computing in Clustered Environments
✍ Scribed by John Cruz; Kihong Park
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 575 KB
- Volume
- 59
- Category
- Article
- ISSN
- 0743-7315
No coin nor oath required. For personal study only.
✦ Synopsis
With the proliferation of workstation clusters connected by high-speed networks, providing efficient system support for concurrent applications engaging in nontrivial interaction has become an important problem. Two principal barriers to harnessing parallelism are: (1) efficient mechanisms that achieve transparent dependency maintenance while preserving semantic correctness and (2) scheduling algorithms that match coupled processes to distributed resources while explicitly incorporating their communication costs. This paper describes a set of performance features and their properties and implementation in a system support environment called DUNES that achieves transparent dependency maintenance IPC, file access, memory access, process creationÂtermination, process relationships under dynamic load balancing. The two principal performance features are pushÂpull-based active and passive end-point caching and communication-sensitive load balancing. Collectively, they mitigate the overhead introduced by the transparent dependency maintenance mechanisms. Communication-sensitive load balancing, in addition, affects the scheduling of distributed resources to application processes where both communication and computation costs are explicitly taken into account. DUNES' architecture endows commodity operating systems with distributed operating system functionality while achieving transparency with respect to their existing application base. DUNES also preserves semantic correctness with respect to single processor semantics. We show performance measurements of a UNIX-based implementation on Sparc and x86 architectures over high-speed LAN environments. We show that significant performance gains in terms of system throughput and parallel application speedup are achievable.