Internet-based applications and their resulting multitier distributed architectures have changed the focus of design for large-scale Internet computing. Internet server applications execute in a horizontally scalable topology across hundreds or thousands of commodity servers in Internet data centers. Increasing scale and power density significantly impacts the data center's thermal properties. Effective thermal management is essential to the robustness of mission-critical applications. Internet service architectures can address multisystem resource management as well as thermal management within data centers. hermal management is an increasingly prominent architectural consideration for high-performance computing. It presents challenges that can apply to chips, servers, racks, and data centers. New classes of applications, such as Internet services and distributed scientific processing, have exacerbated the situation by using horizontal scaling techniques that result in high-density computing environments. [1][2][3] Powerful processors dissipate increasing amounts of waste heat for a given package size. Recent research demonstrates that dynamic thermal management (DTM) can respond to thermal conditions by adaptively adjusting a chip's power-consumption profile on the basis of feedback from temperature sensors. 4,5 Research also shows how to extend DTM to improve processor energy efficiency (see the "Related Work in Dynamic Thermal Management" sidebar, p. 47). These techniques are key elements of thermal design for next-generation server environments, but they address only one aspect of the problem. Several factors are driving the migration of computational power to large arrays (or racks) of servers aggregated in data centers, primarily for Internet-based application services. Power dissipation has grown tremendously in these data centers, and their architecture presents difficult thermal engineering challenges that stem from increasing size and density. 7 Moreover, Internet data centers might use thousands of such racks in the next decade to exploit economies of scale in management, power supply, and security.  center rather than individual servers or chips. Our proposed policies for workload placement promote uniform temperature distribution using active thermal zones. Our detailed computational fluid dynamics (CFD) model of a typical data center can help evaluate the effectiveness of thermal policies through fault-injection simulations and dynamic variations in computational load. To our knowledge, we're the first to deal directly with the interaction of data center thermal architecture and software-resource-management functions. Our approach is part of a broader framework for managing a data center as a utility whose server, router or switch, and storage resources are automatically provisioned and sold according to demand, much as electricity is today. In previous research we described an architecture for largescale on-demand Internet computing infrastructure. 8 Rather than physically wiring each resource into a static topology, the programmable data center (PDC) treats computing, storage, and networking components as shared, virtualized resources that can be dynamically partitioned and allocated across hosted applications on the basis of quality-of-service (QoS) requirements. Example applications include Web-based services, computational batch schedulers, and database services for decision support, data mining, or other applications. Because server and storage resources are generic and interchangeable, the resource manager can reconfigure workload placement to respond to changing load and resource conditions. 8 Features such as service migration, 9 security, and performance isolation 10 let us construct automated data centers with dynamic and adaptive resource provisioning that maintain service levels despite changes in perapplication workload intensity and variety. PDCs are assembled following a regular, horizontally scalable topology built of service cores comprising server storage and networking racks. Each service core has about 1,000 compute nodes and a commensurate-sized storage subsystem connected via a high-speed Ethernet (layer 2) switched fabric. We can aggregate service cores to achieve vast computing and storage capabilities. The PDC architecture supports close to 50,000 rack-mounted servers, petabytes of storage, and tens of terabits per second of ingress and egress traffic.
Reference REF presented a framework for thermal load balancing by applying load monitoring and dynamic workload placement within a data center.
Balance of power: dynamic thermal management for Internet data centers
IEEE Internet Computing
IEEE Internet Computing
Computer Science