All-flash servers, while being widely popular for their high performance and large capacity, can incur significant energy consumption in modern storage systems. Through a motivational study, we discover that the culprit is the inefficiency in the software stack, and existing power-saving methods fail to deliver comparable performance, especially under workload bursts. Guided by the lessons learned, we propose Sandman, a scheduling framework that combines the fast resource scaling mechanism, resource monitoring, and I/O burst detection policies. Experiments show that Sandman reduces average power consumption by up to 39.38% and energy consumption by up to 33.36% while delivering performance comparable (within 5% in corner cases) to the best performance case (the busy-polling stack) in both benchmarks and field workloads.

Educational research has shown that students learn with deeper understanding and retain that understanding for a greater duration when they learn in an environment of inquiry. In order to foster an environment of inquiry in an embedded systems course, we have redesigned the course to give students more and more autonomy with course material as the course progresses. In this paper, we describe the design and preliminary assessment of a semi-autonomous embedded systems course in the computer engineering program at Cal Poly, San Luis Obispo. Preliminary assessment data indicate that the course appears to provide an environment of inquiry for students, but further assessment is required to determine if the semi-autonomous nature of the course increased student understanding and retention of course material.