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On the Model of Computation: Counterpoint: Parallel Programming Wall and Multicore Software Spiral: Denial Hence Crisis

By Uzi Vishkin

Communications of the ACM, Vol. 65 No. 9, Pages 32-34

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Background. the software spiral (SWS) for single CPU cores and the RAM algorithmic model. Andy Grove (Intel's business leader until 2004) termed "software spiral" the exceptionally resilient business model behind general-purpose CPUs. Application software is the defining component of SWS: Code written once could yet benefit from performance scaling of later CPU generations. SWS is comprised of several abstraction levels. The random access machine, or model (RAM) is most relevant for the current Counterpoint Viewpoint (CPV): each serial step of an algorithm features a basic operation taking unit time ("uniform cost" criterion). The RAM has long been the gold standard for algorithms and data structures. Salient aspects of the RAM included: its simplicity; importing from mathematics its own gold standard: mathematical induction for describing algorithms (or their imperative programming code) and proving their correctness; and good enough support by computer systems based on the von Neumann architecture. Other abstraction levels and means included a variety of benchmark suits guiding balanced performance over a range of tasks, software compatibility, object or binary code compatibility, operating systems, and a variety of standards, for example, Figure 1.8 on functional requirements in Hennesey and Patterson.5 The single core CPU business became synonym with making every effort to advancing architectures and optimizing compilers for keeping this SWS on track, making it, as well as the RAM, so resilient, and clear role models for the road ahead.

There Is More to a Lead Model of Computation Than Specialized Efficiencies. The Point Viewpoint (PV) makes a strong case for optimizations based on quantifiable costs at the hardware level. This CPV concurs with applying the PECM model of computation the PV proposes to specialized routines whose use in workloads merits it, as well as to accelerators. However, the foremost problem of today's multicore parallelism is dearth of programmers, since programming such systems is simply too difficult. Imposing the PECM implied optimizations on programmers is unlikely to bring programmers back, thus qualifying its applicability. I am also not aware of demonstrated success of PECM for general-purpose programming. Using computer architecture lingo, the upshot of the current paragraph is that architects of manycore platforms must recognize not only the so-called "memory wall" and "energy wall," but also a "parallel programming wall."


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