Vector-supercomputers

Today, the field of high-speed computers and supercomputing applications is dominated by the vector-processor architecture. This paper gives a survey on the architectural principles of vector computers like segmentation, pipelining, and chaining as well as on the spectrum of real systems available in the market. It illuminates the potentiality and the limitations of vectorization strategies. Recent developments towards multi-vectorcomputer systems give impact to new supercomputing concepts balancing vectorization versus parallel computation by exploiting multitasking principles. Covering a wide spectrum of applications vector-supercomputers are making relevant contributions to the progress in scientific research and technology.     

Microtasking as a complement to macrotasking

The ECMWF weather model runs daily as a time critical application. Acceptable elapsed times are achieved by multitasking the code on a CRAY X-MP/48. This is done at a high level giving rise to large tasks. Investigations have been carried out to tackle inefficiencies by microtasking at a low level so that the code can take advantage of any idle processors which may become available.     

Multitasking: Experience with applications on a CRAY X-MP

On the multiprocessor vector-supercomputer CRAY X-MP, parallelism—beyond vectorization—can be exploited on the programming language level by two multitasking strategies: macrotasking and, more recently, microtasking. In this paper, multitasking results and experiences are presented which have been gained by applying these two implemented modes to linear-algebra and non-numerical algorithms as well as to a large fluid-flow simulation code. While comparing the concepts and realizations of macrotasking and microtasking, the features, tools, and problems of multitasking programming and the potential user benefit of these parallel processing techniques are discussed.     

Using multiple CPUs for problem solving: Experiences in multitasking on the CRAY X-MP/48

The integration of vector computers into multiprocessor configurations allows the use of multiple high-speed processors in parallel for one program. There are two aspects which are considered to be important for an efficient use of multiprocessor configurations. First, the flexibility, speed and user friendliness of the available synchronization and communication primitives, and second, the user problems in detecting data dependencies and in translating programs correctly into the parallel form required by the system. This paper is intended to give an overview of our experiences in multitasking using up to four CPUs of a CRAY X-MP/48. The results gained by macrotasking and microtasking will be compared for program kernels and real-life application programs. Special attention is paid to the difficulties of using more than two CPUs in parallel.