Abstract-While modern processors offer a wide spectrum of software-controlled power modes, most datacenters only rely on Dynamic Voltage and Frequency Scaling (DVFS, a.k.a. P-states) to achieve energy efficiency. This paper argues that, in the case of datacenter workloads, DVFS is not the only option for processor power management. We make the case for per-core power gating (PCPG) as an additional power management knob for multi-core processors. PCPG is the ability to cut the voltage supply to selected cores, thus reducing to almost zero the leakage power for the gated cores. Using a testbed based on a commercial 4-core chip and a set of real-world application traces from enterprise environments, we have evaluated the potential of PCPG. We show that PCPG can significantly reduce a processor's energy consumption (up to 40%) without significant performance overheads. When compared to DVFS, PCPG is highly effective saving up to 30% more energy than DVFS. When DVFS and PCPG operate together they can save up to almost 60%.
Multicore architectures are ruling the recent microprocessor design trend. This is due to different reasons: better performance, threadlevel parallelism bounds in modern applications, ILP diminishing returns, better thermal/power scaling (many small cores dissipate less than a large and complex one); and, ease and reuse of design.This paper presents a thorough evaluation of multicore architectures. The architecture we target is composed of a configurable number of cores, a memory hierarchy consisting of private L1 and L2, and a shared bus interconnect. We consider parallel shared memory applications. We explore the design space related to the number of cores, L2 cache size and processor complexity, showing the behavior of the different configurations/applications with respect to performance, energy consumption and temperature. Design tradeoffs are analyzed, stressing the interdependency of the metrics and design factors. In particular, we evaluate several chip floorplans. Their power/thermal characteristics are analyzed and they show the importance of considering thermal effects at the architectural level to achieve the best design choice.
In this paper we introduce CACTI-D, a significant enhancement of CACTI 5.0. CACTI-D adds support for modeling of commodity DRAM technology and support for main memory DRAM chip organization. CACTI-D enables modeling of the complete memory hierarchy with consistent models all the way from SRAM based L1 caches through main memory DRAMs on DIMMs. We illustrate the potential applicability of CACTI-D in the design and analysis of future memory hierarchies by carrying out a last level cache study for a multicore multithreaded architecture at the 32nm technology node. In this study we use CACTI-D to model all components of the memory hierarchy including L1, L2, last level SRAM, logic process based DRAM or commodity DRAM L3 caches, and main memory DRAM chips. We carry out architectural simulation using benchmarks with large data sets and present results of their execution time, breakdown of power in the memory hierarchy, and system energy-delay product for the different system configurations. We find that commodity DRAM technology is most attractive for stacked last level caches, with significantly lower energy-delay products.
Abstract-Multicore architectures have been ruling the recent microprocessor design trend. This is due to different reasons: better performance, thread-level parallelism bounds in modern applications, ILP diminishing returns, better thermal/power scaling (many small cores dissipate less than a large and complex one), and the ease and reuse of design. This paper presents a thorough evaluation of multicore architectures. The architecture that we target is composed of a configurable number of cores, a memory hierarchy consisting of private L1, shared/private L2, and a shared bus interconnect. We consider a benchmark set composed of several parallel shared memory applications. We explore the design space related to the number of cores, L2 cache size, and processor complexity, showing the behavior of the different configurations/applications with respect to performance, energy consumption, and temperature. Design trade-offs are analyzed, stressing the interdependency of the metrics and design factors. In particular, we evaluate several chip floorplans. Their power/thermal characteristics are analyzed, showing the importance of considering thermal effects at the architectural level to achieve the best design choice.
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