The Multiple Instruction Stream Processor (MISP) architecture introduces the sequencer as a new class of architectural resource, and provides a minimalist user-level MIMD instruction set extension for application programs to directly control execution of concurrent instruction streams on these sequencers. As with classic architectural resources, namely, registers and memory, the sequencer architectural resource can be subject to virtualization. This paper details the idea of Sequencer Virtualization (SV), a foundational architectural support to decouple architectural virtual sequencers from physical sequencers. SV enables more efficient utilization of sequencer resources at the microarchitectural level while maintaining a consistent programming interface at the architectural level. To evaluate the key tradeoffs for SV, we conduct extensive experiments by implementing a prototype SV system using a custom firmware on a large-scale multiprocessor system. Using the prototype SV system, we demonstrate that SV improves efficiency in sequencer utilization while incurring little performance overhead. In particular, for a set of real multithreaded workloads, SV can significantly improve sequencer utilization, achieving an average of 32% better wall-clock performance than MISP without SV support in a multi-programming environment.

As multiple processor systems become more widely accepted the importance of parallel programming increases. In this paper, approaches to the design and analysis of parallel algorithms are investigated. Through several examples, the importance of interprocessor communication in parallel processing is demonstrated. Various techniques that are applicable in the design and analysis of parallel algorithms are examined with emphasis on those techniques that incorporate communication aspects. The paper discusses several models of synchronous and asynchronous parallel computation and their use in analyzing algorithms. Relatively primitive methodologies for designing parallel algorithms are discussed and the need for more general and practical methodologies is indicated.

As multiple computer systems become more widely accepted, the importance of parallel programming increases. In this paper, approaches to the design and analysis of parallel algorithms are investigated. Through several examples the importance of interprocessor communication in parallel processing is demonstrated. Various techniques that are applicable in the design and analysis of parallel algorithms are examined with emphasis on those techniques that incorporate communication aspects. The paper discusses several models of synchronous and asynchronous parallel computation and their use in analyzing algorithms. Relatively primitive methodologies for designing parallel algorithms are discussed and the need for more general and practical methodologies is indicated.