24 research outputs found
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Dataparallel C : a SIMD programming language for multicomputers
Dataparallel C is a SIMD extension to the standard C programming language. It is derived from the original C* language developed by Thinking Machines Corporation.. We have nearly completed a third-generation Dataparallel C compiler, which transforms Dataparallel C programs into SPMD-style C code suitable for compilation and execution on NCUBE multicomputers. In this paper we elaborate on the characteristics and strengths of dataparallel programming languages. We summarize the syntax and semantics of Dataparallel C, present six benchmark programs, and document the performance of these programs executing on the NCUBE 3200 multicomputer. Our work demonstrates that SIMD source programs can achieve reasonable speedup when compiled and executed on MIMD computers.Key Words : compiler, data parallel, hypercube, MIMD, multicomputer, programming language, SIM
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A production-quality C* compiler for a hypercube multicomputer
We describe our third generation C* compiler for a hypercube multicomputer. This production quality compiler features a full implementation of the language, including general pointer-based communication and support for separate compilation. The compiler incorporates new optimizations and utilizes an improved set of communication primitives. It supports a variety of standard domain decomposition primitives, and it also allows the programmer to specify a custom mapping of data to the distributed memories of the hypercube. The performance of this compiler on benchmark programs demonstrates that high efficiency can be achieved executing SIMD code on multicomputer architectures
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Data-parallel programming on MIMD computers
We are convinced that the combination of data-parallel languages and MIMD hardware can make an important contribution to high speed computing. The data-parallel paradigm is a natural way to solve a large number of problems arising in science and engineering. Data-parallel programs are easier to design, implement, and debug than programs written in a MIMD language. For their part, the existence of multiple control units on MIMD computers can allow loosely-synchronous programs to execute more efficiently than they would on a SIMD architecture. In this paper we provide empirical evidence to support these assertions. We describe the implementation of two compilers for the data-parallel programming language C*. One compiler generates code for the NCUBE 3200 hypercube multicomputer, the other generates code for the Sequent Balance 21000 multiprocessor. We have compiled and executed a suite of C* programs on these two systems, and we present the execution times and speedups achieved by these programs
Discordant identification of pediatric severe sepsis by research and clinical definitions in the SPROUT international point prevalence study
Introduction: Consensus criteria for pediatric severe sepsis have standardized enrollment for research studies. However, the extent to which critically ill children identified by consensus criteria reflect physician diagnosis of severe sepsis, which underlies external validity for pediatric sepsis research, is not known. We sought to determine the agreement between physician diagnosis and consensus criteria to identify pediatric patients with severe sepsis across a network of international pediatric intensive care units (PICUs). Methods: We conducted a point prevalence study involving 128 PICUs in 26 countries across 6 continents. Over the course of 5 study days, 6925 PICU patients <18 years of age were screened, and 706 with severe sepsis defined either by physician diagnosis or on the basis of 2005 International Pediatric Sepsis Consensus Conference consensus criteria were enrolled. The primary endpoint was agreement of pediatric severe sepsis between physician diagnosis and consensus criteria as measured using Cohen's ?. Secondary endpoints included characteristics and clinical outcomes for patients identified using physician diagnosis versus consensus criteria. Results: Of the 706 patients, 301 (42.6 %) met both definitions. The inter-rater agreement (? ± SE) between physician diagnosis and consensus criteria was 0.57 ± 0.02. Of the 438 patients with a physician's diagnosis of severe sepsis, only 69 % (301 of 438) would have been eligible to participate in a clinical trial of pediatric severe sepsis that enrolled patients based on consensus criteria. Patients with physician-diagnosed severe sepsis who did not meet consensus criteria were younger and had lower severity of illness and lower PICU mortality than those meeting consensus criteria or both definitions. After controlling for age, severity of illness, number of comorbid conditions, and treatment in developed versus resource-limited regions, patients identified with severe sepsis by physician diagnosis alone or by consensus criteria alone did not have PICU mortality significantly different from that of patients identified by both physician diagnosis and consensus criteria. Conclusions: Physician diagnosis of pediatric severe sepsis achieved only moderate agreement with consensus criteria, with physicians diagnosing severe sepsis more broadly. Consequently, the results of a research study based on consensus criteria may have limited generalizability to nearly one-third of PICU patients diagnosed with severe sepsis
Congruent strategies for carbohydrate sequencing. 3. OSCAR: An algorithm for assigning oligosaccharide topology from MSn data
This is the third in a sequence of reports devoted to the development of congruent strategies for carbohydrate sequencing. Two previous reports outlined the strategies for observing structural detail from MSn data and introduced tools that compile, search, and compare fragment spectra in a bottom-up approach to oligosaccharide sequencing. In this third report, we. introduce the operational details of an algorithm that we define as the Oligosaccharide Subtree Constraint Algorithm (OSCAR). This algorithm assimilates analyst-selected MSn ion fragmentation pathways into oligosaccharide topology (branching and linkage) using what may be considered a top-down sequencing strategy. Guided by a series of logical constraints, this de novo algorithm provides molecular topology without presumed biosynthetic constraints or external comparisons. In this introductory study, OSCAR is applied to a series of permethylated oligomers and isomeric glycans, and topologies are assigned in a few hundredths of a second