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D Findings and Recommendations from The Future of Computing Performance: Game Over or Next Level? T he following findings and recommendations are repeated from the National Research Council's report, The Future of Computing Performance: Game Over or Next Level?1 systems not only by parallel-systems experts but also by typical programmers. Focus long-term efforts on rethinking of the canonical computing "stack"--applications, programming language, compiler, runtime, virtual machine, Findings: operating system, hypervisor, and architecture--in The information technology sector itself and most light of parallelism and resource-management other sectors of society--for example, manufacturing, challenges. financial and other services, science, engineering, Invest in research on and development of parallel education, defense and other government services, and architectures driven by applications, including entertainment--have grown dependent on continued enhancements of chip multiprocessor systems and growth in computing performance. conventional data-parallel architectures, cost-effective After many decades of dramatic exponential growth, designs for application-specific architectures, and single processor performance is increasing at a much support for radically different approaches. lower rate, and this situation is not expected to Invest in research and development to make computer improve in the foreseeable future. systems more power-efficient at all levels of the The growth in the performance of computing system, including software, application-specific systems--even if they are multiple-processor parallel approaches, and alternative devices. Such efforts systems--will become limited by power consumption should address ways in which software and system within a decade. architectures can improve power efficiency, such as by There is no known alternative to parallel systems for exploiting locality and the use of domain-specific sustaining growth in computing performance; execution units. R&D should also be aimed at making however, no compelling programming paradigms for logic gates more power-efficient. Such efforts should general parallel systems have yet emerged. address alternative physical devices beyond incremental improvements in today's CMOS circuits. Recommendations: To promote cooperation and innovation by sharing, Invest in research in and development of algorithms encourage development of open interface standards for that can exploit parallel processing. parallel programming rather than proliferating Invest in research in and development of programming proprietary programming environments. methods that will enable efficient use of parallel Invest in the development of tools and methods to transform legacy applications to parallel systems. Incorporate in computer science education an 1 increased emphasis on parallelism, and use a variety of NRC, 2011, The Future of Computing Performance: Game methods and approaches to better prepare students for Over or Next Level?, Washington, D.C.: The National Academies Press (available online at the types of computing resources that they will id=12980). encounter in their careers. 67

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