While at Caltech, one of my major activities involved studying the parallel software and algorithms needed by large scale scientific and engineering computation [Angus:90a], [Fox:88a], [Fox:94a]. One of my interests in moving to Syracuse was to extend this approach, but focus on industrial and not academic applications. This activity, now called InfoMall [Fox:93c], [Mills:93a], [Mills:94a] is supported by New York State and aims to accelerate the introduction of High Performance Computing and Communication technology into the State's industry. It has three major components. Firstly, it involves those industries that uses computers (i.e., the applications of HPCC, which are described later in this section). Secondly, InfoMall seeks to create (enhance) an HPCC software industry in the State, and Section 3 describes issues connected with this activity. The final component of InfoMall is devoted to training and is especially centered in the mid-Hudson (Kingston, Poughkeepsie, and Fishkill) area of New York where some 10,000 former IBM engineers are looking for new job opportunities---InfoMall aids those interested in HPCC careers. Such pools of engineers exist in many parts of the country, a byproduct of the major restructuring in aerospace, manufacturing, computer, and other industries. This national resource indicates that we have the people to implement the integration of HPCC into the country's industry. We ``only'' need to identify the viable opportunities and the necessary funds (venture capital) to implement them.
Now, we discuss which opportunities are in fact viable---this returns to the first component of InfoMall---what are the relatively near term industrial applications of HPCC. The first phase of our New York State project involved a significant survey reported in Tables 1 to 6, which divides possible applications into four major areas, and then in more refined fashion, 33 classes. The good news is that as summarized in Table 2 and Column 2 of Tables 1 to 4, we already have the necessary, if not the most productive, software technology needed to implement all of these applications. Further, extensive computer science research tested in grand challenge and other academic and research implementations, has given us excellent parallel algorithms. Again, a good argument can be made in every entry in Tables 1 to 5, that HPCC will make a difference and improve the performance and/or competitiveness of the associated industry. Nevertheless, only in a few cases will the return on investment justify the work involved in implementing the HPCC application. This conclusion is explained in [Fox:92e] [Mills:94b], [Fox:94b], [Fox:94c], and here we can only summarize and illustrate this conclusions. Note that the four application classes in Table 1 are:
Originally, I had envisioned a major InfoMall activity in the Simulation (A), as this was the natural counterpart to my personal academic activity at Caltech, as well the broad national endeavor in the Federal Grand Challenge Initiative. However, the clear near-term value of HPCC simulations in the research applications is not so obvious in industry. We can only illustrate this conclusion with one example here. Consider the application of HPCC to manufacturing---an area of exceptional importance and promise. One can use HPCC for one or more of the components of manufacturing---such as the first three classes of Table 1---fluid flow, structural and electromagnetic simulation. However, these are in general quite small parts of the whole manufacturing and design process. Thus, we see Amdahl's law applied to manufacturing---if simulation is (for example) 10% of the design cycle, then parallelizing this one part can give at best a speedup of 1.1 We are still dominated by the 90% remaining ``sequential'' part of the process to which we have not applied HPCC. Thus, the best opportunity for HPCC lies in its integration into the entire manufacturing operations. This will enable agile manufacturing and as components of this, concurrent engineering and multidisciplinary analysis and design. Just considering the latter, this is as shown in Figure 1 a challenging but in principle, perfectly feasible integration task. However, the real world makes it ``very hard''. Thus, components of Figure 1 are existing one million codes (such as NASTRAN) which not only have to be parallelized, but also integrated with other major software packages. Perhaps more important difficulties are nontechnical issues. Most manufacturing companies face restructuring, cutbacks and/or fierce global competition. Agile manufacturing implies not only technology investment and (risky) development, but remaking the whole engineering process. Thus, we cannot address manufacturing just as an HPCC technology problem, but many national infrastructure and education issues are involved. I see this area as an exciting long-term area for HPCC, which need major government investment as industry will find it hard to justify the investment based on a typical one to three year return.
Figure 1: Software Structure for Multidisciplinary Analysis and Design
Returning to the survey of Tables 1 to 6, we found (in New York State) much more near-term promise in the information related applications (B), (C), and (D). There are several reasons for this. The simplest reason is phase space---information processing always has been the dominant use of computers in business and this is likely to be accentuated and not decreased in the future. Further, one ``only'' needs to parallelize a few software pieces (e.g., implement a parallel database) to enable a large set of applications. Although very challenging, this task is well underway commercially with, for instance, Oracle 7.1 supporting parallel query. In contrast, simulation has no single ``killer application'' and each piece of software is typically only used in specialized fashion. The National Information Infrastructure (NII) applications in (C), parallel servers on high-speed networks, have another advantageous feature---namely they are ``new'', that is, involve developing software from scratch and not as in many simulation applications, porting existing sequential codes. It is clearly easier to justify the investment in parallel machines for new software systems than for the cases when porting of large existing systems is involved.
This is a rambling story and incomplete to boot---what do we deduce from it? I concluded that information processing is the most promising role for the HPCC industry. Correspondingly, I have redirected our New York State funded activities in this area. Our project must focus on relatively near term opportunities to satisfy its (funded) economic development goals of job creation. However, the federal government needs to support both simulation and information processing related technologies---HPCC simulation will be critical in the long run and not an easy investment for industry. Thus, I support the broadening of the Grand Challenges to include a new set of National Challenges focussed on information based applications. This should not only feature NII applications (C) (and parts of (D)), but also the basic information analysis cases in Table 3. In fact, as the NII does not yet exist except as the comparatively low bandwidth internet, industrial interest will initially center on those cases in Tables 3 and 5, which do not require the pervasive multimegabit/second network for everybody, everywhere and at every time promised by the NII.