Energy-Efficient Programmable Accelerators

点击翻译按钮获取中文摘要

For 50 years computing systems have benefited from exponentially increasing performance per dollar. The first microprocessor was fabricated using 10 micrometer transistors in 1971 while recent designs have been manufactured using 14 nanometer transistors. The resulting five-orders of magnitude increase in transistor density combined with three orders of magnitude increase in clock frequency has enabled computing to change from handling only simple business calculations to supporting machine learning algorithms rivaling humans in accuracy and led to the emerging "internet of things" that promises to broadly increase convenience and productivity. However, the rate of transistor scaling will likely slow significantly after the 5nm process node threatening such visions for the future. Indeed, transistor threshold voltage scaling essentially stopped a decade ago resulting in stagnant clock frequencies, a shift to multicore and more recent concerns about "dark silicon". While alternative technologies (e.g., quantum computing) may provide excellent long term solutions these will take decades to fully develop resulting in a "fallow period" during which computing system capability will stagnate unless alternatives are found. In principle, computing system capability can be improved by orders of magnitude by exploiting specialized hardware. This promise comes at the expense of reduced flexibility and/or difficult programming models. The long-term goal of this research program is to enable order-of-magnitude improvements in computing capability per dollar versus today's computing hardware for diverse software applications. Such an improvement will almost certainly benefit business and society in general. For example, such increases could benefit society enabling more sophisticated machine learning to be applied embedded internet-of-things devices. An order of magnitude gain in computing capability could translate into the difference between a IoT enabled fridge that emails you if the milk is about to reach its use before date, and one that recognizes you are getting bored with your food choices and suggests a shopping list based upon past preferences and your family's health goals. This research program will tackle these goals by exploring both software and hardware approaches to improve the tradeoff between ease of software development and increasing computing capability by exploiting specialized hardware. The expected outcome is insights into how best to structure future computing systems so that the currently robust software industry remains viable past the end of Moore's Law. Canada will benefit because there is a growing number of computer hardware (Intel, AMD, Qualcomm) and software (Electronic Arts, IBM, Microsoft) companies with an R&D presence here that can readily leverage these insights.