If a program is not executed as expected, we say that a semantic error has occurred in the program. As is well known, semantic errors sometimes appear in a program because the modification intention was not correctly ...
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If a program is not executed as expected, we say that a semantic error has occurred in the program. As is well known, semantic errors sometimes appear in a program because the modification intention was not correctly reflected in the new configuration. In order to avoid as many semantic errors as possible, as well as to efficiently locate errors, the authors are developing a semantic configuration management (SCM) model that is capable of efficiently performing various analyses of programs in a unified framework. Previously, the following techniques have been proposed in the SCM model: an analysis technique for detecting infeasible paths (IFPs) from the program, and an analysis technique for generating various kinds of slices in a unified framework. This paper proposes a technique for accurately computing program slices using the IFPs in the SCM model. Next, it proposes a technique for improving the accuracy of detecting semantic errors during merging of several modifications by using accurate program slices. In addition, new applications are proposed for the various slices.
In this paper the design of systolic array processors for computing 2-dimensional Discrete Fourier Transform (2-D DFT) is considered. We investigated three different computational schemes for designing systolic array ...
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In this paper the design of systolic array processors for computing 2-dimensional Discrete Fourier Transform (2-D DFT) is considered. We investigated three different computational schemes for designing systolic array processors using systematic approach. The systematic approach guarantees to find optimal systolic array processors from a large solution space in terms of the number of processing elements and I/O channels, the processing time, topology, pipeline period, etc. The optimal systolic array processors are scalable, modular and suitable for VLSI implementation. An application of the designed systolic array processors to the prime-factor DFT is also presented.
This paper describes the implementation of transmission-line matrix (TLM) method algorithms on a massively parallel computer (DECmpp 12000), the technique of distributed computing in the UNIX environment, and the comb...
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This paper describes the implementation of transmission-line matrix (TLM) method algorithms on a massively parallel computer (DECmpp 12000), the technique of distributed computing in the UNIX environment, and the combination of TLM analysis with Prony's method as well as with autoregressive moving average (ARMA) digital signal processing for electromagnetic field modelling. By combining these advanced computation techniques, typical electromagnetic field modelling of microwave structures by TLM analysis can be accelerated by a few orders of magnitude.
Serialization and deserialization dominate the state transfer time of serverless workflows, leading to substantial performance penalties when executing various serverless workflow applications. We identify the key rea...
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Serialization and deserialization dominate the state transfer time of serverless workflows, leading to substantial performance penalties when executing various serverless workflow applications. We identify the key reason for serialization and deserialization as a lack of ability to efficiently access the (remote) memory of another function. To this end, we propose RMMap, an OS primitive for remote memory map, which allows a serverless function to directly access the memory of another function, even if it is located remotely. RMMap is the first to completely eliminate serialization and deserialization overhead when transferring states between any pairs of functions in (unmodified) serverless workflows. To make remote memory map efficient and feasible, we co-design it with modern networking (RDMA), OS, language runtime, and serverless platform. Evaluations using real-world serverless workloads show that integrating RMMap with Knative reduces the serverless workflow execution time on Knative by up to 2.6 × and improves resource utilizations by 86.3%.
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