Tom W. Keller

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<italic>This paper examines the problem of data placement in Bubba, a highly-parallel system for data-intensive applications being developed at MCC. &#8220;Highly-parallel&#8221; implies that load balancing is a critical performance issue. &#8220;Data-intensive&#8221; means data is so large that operations should be executed where the data resides. As a(More)
The combination of increasing component power consumption, a desire for denser systems, and the required performance growth in the face of technology-scaling issues are posing enormous challenges for powering and cooling of server systems. The challenges are directly linked to the peak power consumption of servers.Our solution, <i>Power Shifting</i>,(More)
I n the past, energy-aware computing was primarily associated with mobile and embedded computing platforms. Servers—high-end, multiprocessor systems running commercial workloads—typically included extensive cooling systems and resided in custom-built rooms for high-power delivery. In recent years, however, as transistor density and demand for computing(More)
Existing techniques manage power for the main memory by passively monitoring the memory traffic, and based on which, predict when to power down and into which low-power state to transition. However, passively monitoring the memory traffic can be far from being effective as idle periods between consecutive memory accesses are often too short for existing(More)
The IBM POWER6e microprocessor chip supports advanced, dynamic power management solutions for managing not just the chip but the entire server. The design facilitates a programmable power management solution for greater flexibility and integration into systemand data-center-wide management solutions. The design of the POWER6 microprocessor provides(More)
In today's data centers, precisely controlling server power consumption is an essential way to avoid system failures caused by power capacity overload or overheating due to increasingly high server density. While various power control strategies have been recently proposed, existing solutions are not scalable to control the power consumption of an entire(More)
In today's data centers, precisely controlling server power consumption is an essential way to avoid system failures caused by power capacity overload or overheating due to increasingly high server density. While various power control strategies have been recently proposed, existing solutions are not scalable to control the power consumption of an entire(More)
Energy is becoming a critical resource to not only small battery-powered devices but also large server systems, where high energy consumption translates to excessive heat dissipation, which, in turn, increases cooling costs and causes servers to become more prone to failure. Main memory is one of the most energy-consuming components in many systems. In this(More)
Applications on today's high-end systems typically make varying load demands over time. A single application may have many different phases during its lifetime, and workload mixes show interleaved phases. Memory-intensive work or phases may exhibit performance saturation at frequencies below the maximum possible for the processors due to the disparity(More)