SISD

Abstract: Very high-speed computers may be classified as follows: 1) Single Instruction Stream-Single Data Stream (SISD) 2) Single Instruction Stream-Multiple Data Stream (SIMD) 3) Multiple Instruction Stream-Single Data Stream (MISD) 4) Multiple Instruction Stream-Multiple Data Stream (MIMD). "Stream," as used here, refers to the sequence of data or instructions as seen by the machine during the execution of a program. The constituents of a system: storage, execution, and instruction handling (branching) are discussed with regard to recent developments and/or systems limitations. The constituents are discussed in terms of concurrent SISD systems (CDC 6600 series and, in particular, IBM Model 90 series), since multiple stream organizations usually do not require any more elaborate components. Representative organizations are selected from each class and the arrangement of the constituents is shown.

Abstract: A Parallel RISC computer system is provided by a multi-mode dynamic multi-mode parallel processor array with one embodiment illustrating a tightly coupled VLSI embodiment with an architecture which can be extended to more widely placed processing elements through the interconnection network which couples multiple processors capable of MIMD mode processing to one another with broadcast of instructions to selected groups of units controlled by a controlling processor. The coupling of the processing elements logic enables dynamic mode assignment and dynamic mode switching, allowing processors operating in a SIMD mode to make maximum memory and cycle time usage. On and instruction by instruction level basis, modes can be switched from SIMD to MIMD, and even into SISD mode on the controlling processor for inherently sequential computation allowing a programmer or complier to build a program for the computer system which uses the optimal kind of parallelism (SISD, SIMD, MIMD). Furthermore, this execution, particularly in the SIMD mode, can be set up for running applications at the limit of memory cycle time. With the ALLNODE switch and alternatives paths a system can be dynamically achieved in a few cycles for many many processors. Each processing element and memory and has MIMD capability the processor's an instruction register, condition register and program counter provide common resources which are used in MIMD and SIMD. The program counter become a base register in SIMD mode.

Abstract: Horizon is a scalable shared-memory Multiple Instruction stream - Multiple Data stream (MIMD) computer architecture independently under study at the Supercomputing Research Center (SRC) and Tera Computer Company. It is composed of a few hundred identical scalar processors and a comparable number of memories, sparsely embedded in a three-dimensional nearest-neighbor network. Each processor has a horizontal instruction set that can issue up to three floating point operations per cycle without resorting to vector operations. Processors will each be capable of performing several hundred Million Floating Point Operations Per Second (FLOPS) in order to achieve an overall system performance target of 100 Billion (1011) FLOPS.This paper describes the architecture of the processor in the Horizon system. In the fashion of the Denelcor HEP, the processor maintains a variable number of Single Instruction stream - Single Data stream (SISD) processes, which are called instruction streams. Memory latency introduced by the large shared memory is hidden by switching context (instruction stream) each machine cycle. The processor functional units are pipelined to achieve high computational throughput rates; however, pipeline dependencies are hidden from user code. Hardware mechanisms manage the resources to guarantee anonymity and independence of instruction streams.

Abstract: A server migration tool used to construct data center migration scenarios allowing for a user to rapidly manipulate a large number of input parameters required to describe a transformation from one data center configuration to a new data center configuration. The tool then performs the transformation and allows the user to interact with new data center configuration to understand its performance. A novel parameterization, speed independent service demand (SISD), greatly facilitates scaling performance metrics between different hardware platforms.