We review possible and probable industrial applications of HPCC focusing on the software and hardware issues. Thirty-three separate categories are illustrated by detailed descriptions of ve areas|computational chemistry Monte Carlo methods from physics to economics manufacturing, and computational uid dynamics command and control, or crisis management and multimedia services to client computers and settop boxes. The hardware varies from tightly-coupled parallel supercomputers to heterogeneous

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... stributed systems. The software models span HPF and data parallelism, to distributed information systems and object/data ow parallelism on the Web. We nd that in each case, it is reasonably clear that \HPCC works in principle," and postulate that this knowledge can be used in a new generation of software infrastructure based on the WebWindows approach, and discussed in an accompanying paper. { { on supercomputers etc.) with and technologies (PC, Web) low-end but widely used applications Bottom-up Approach (Command Control Manufacturing etc.) Involving integration and capabilities Metaproblems high-end technologies (MPI, HPF,..) and low-end of high-high-end applications (3D CFD Figure 1: Integration of Grand Challenges and Pervasive T echnologies \integrated" metaproblems|or national challenges. In the analysis that follows, we g r o u p p o ssible industrial uses of parallel computers into 33 broad classes, which include both Grand and National Challenges. In the nal section, we describe ve particular applications to illustrate the analysis of the relevance of HPCC in their solution. These include Grand Challenges, such as Monte Carlo simulation, computational uid dynamics, and molecular dynamics as well as National Challenges, such a s m ultimedia (Web) information systems, manufacturing, and command and control. The latter three areas are \metaproblems" (de ned precisely in Section 2), which integrate several distributed applications including component grand challenges, such as vehicle and process simulation in manufacturing, and weather prediction in command and control. The bottom-up approach of Figure 1 is proposed so that one can build HPCC applications and software on a commercially viable base Fox:95k]. There are two such natural technology springboards| rstly, shared memory multiprocessors, and secondly, Web or distributed computing. The rst choice leads to the interesting distributed shared memory environments, whereas the second is naturally a message passing environment. We expect that both these \viable bases" should and will be explored. One important feature of the broader distributed computing base is that it \by de nition" includes \everything," and so one can build complete metaproblems in terms of a single technology framework. From this point of view, this paper can be considered as a summary of results and requirements for \top of the pyramid" software, algorithms, and applications that need to be used in designing and building the bottom-up HPCC technology. Section 2 reviews our general study of the structure of problems, as this is helpful in understanding the appropriate hardware and software system in each case. In Section 3, we show how the di erent problem categories or architectures are addressed by parallel software systems with di erent capabilities. We give illustrative examples, but not an exhaustive list of existing software systems with these characteristics. We consider High Performance Fortran and its extensions as a data parallel language message passing systems, such as those supplied with commercial multicomputers as well as approaches to software integration. In Section 2, we point that our old classi cation of problems omitted metaproblems|problems built up from several components|each of which could have its own parallelization issues.