This paper presents PARD, a programmable architecture for resourcing-on-demand that provides a new programming interface to convey an application's high-level information like quality-of-service requirements to the hardware. PARD enables new functionalities like fully hardware-supported virtualization and differentiated services in computers. PARD is inspired by the observation that a computer is inherently a network in which hardware components communicate via packets (e.g., over the NoC or PCIe). We apply principles of software-defined networking to this intra-computer network and address three major challenges. First, to deal with the semantic gap between high-level applications and underlying hardware packets, PARD attaches a high-level semantic tag (e.g., a virtual machine or thread ID) to each memory-access, I/O, or interrupt packet. Second, to make hardware components more manageable, PARD implements programmable control planes that can be integrated into various shared resources (e.g., cache, DRAM, and I/O devices) and can differentially process packets according to tag-based rules. Third, to facilitate programming, PARD abstracts all control planes as a device file tree to provide a uniform programming interface via which users create and apply tag-based rules.

Datacenters consolidate diverse applications to improve utilization. However when multiple applications are co-located on such platforms, contention for shared resources like Networks-on-Chip (NoCs) can degrade the performance of latency-critical online services (high-priority applications). Recently proposed bufferless NoCs have the advantages of requiring less area and power, but they pose challenges in quality-of-service (QoS) support, which usually relies on buffer-based virtual channels (VCs). We propose QBLESS, a QoS-aware bufferless NoC scheme for datacenters. QBLESS consists of two components: a routing mechanism (QBLESS-R) that can substantially reduce flit deflection for high-priority applications, and a congestion-control mechanism (QBLESS-CC) that guarantees performance for high-priority applications and improves overall system throughput. We use trace-driven simulation to model a 64-core system, finding that when compared to BLESS, a previous state-of-the-art bufferless NoC design, QBLESS improves performance of high-priority applications by an average of 33.2%.