With the slowing of technology scaling, the only known way to further improve computer system performance under energy constraints is to employ hardware accelerators. Already today, many chips in mobile , edge and cloud computing concurrently employ multiple accelerators in what we call accelerator-level parallelism (ALP). For the needed benefits of ALP to spread to computer systems more broadly, we herein charge the community to develop better "best practices" for: targeting accelerators, managing accelerator concurrency, choreographing inter-accelerator communication, and productively programming accelerators .
Future applications demand more performance, but technology advances have been faltering. A promising approach to further improve computer system performance under energy constraints is to employ hardware accelerators. Already today, mobile systems concurrently employ multiple accelerators in what we call accelerator-level parallelism (ALP). To spread the benefits of ALP more broadly, we charge computer scientists to develop the science needed to best achieve the performance and cost goals of ALP hardware and software .
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With the slowing of technology scaling, the only known way
Future applications demand more performance, but technology advances have been faltering. A promising approach
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many chips in mobile , edge and cloud computing
mobile systems
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For the needed
To spread the
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to spread to computer systems
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herein charge the community to develop better "best practices" for: targeting accelerators, managing accelerator concurrency, choreographing inter-accelerator communication, and productively programming accelerators
charge computer scientists to develop the science needed to best achieve the performance and cost goals of ALP hardware and software