With Moore’s law nearing its death, heterogeneous computing promises a new solution to the need for speed.
With Moore’s law nearing its death, computer scientists are finding integrative approaches to realizing ongoing increases in computing processing speed.
As Moore’s law approaches 60 years old, computer science struggles to keep up with doubling the number of transistors in integrated circuits every 2 years.Now, heterogeneous computing promises a new solution to the need for speed.
The complexity of such a system arises in hardware and software. From a hardware perspective, simply arranging all of the devices to work together is challenging. For the software, Yang points out that “different types of computing tasks are most efficient on different types of computing clusters, like CPU compute resources or GPU clusters, and they have different kinds of managing systems that we need to integrate in one single platform.
Some applications, such as robotics, use physically separated computing resources, and that creates other challenges. “In a robotics scenario, the computing power on the robot is very limited, and the bandwidth between the robotics and cloud server is also limited,” Yang says. Plus, many robots must run a family of algorithms, such as ones for movement, vision and voice processing, and more.
In the future, Yang and his colleagues plan to make heterogenous computing available for more areas of study, from new applications in science to social purposes, such as biological/ astronomical findings, economical predictions, and intelligent manufacturing. As Yang says, “In every case, we want to develop high-efficiency computing across multiple clusters to help people address any question.
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