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Energy Conservation in Datacenters through Cluster Memory Management and Barely-Alive Memory Servers
"... As a result of current resource provisioning schemes in Internet services, servers end up less than 50 % utilized almost all the time. At this level of utilization, the servers ’ energy efficiency is less than half their efficiency at peak utilization. A solution to this problem could be consolidati ..."
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As a result of current resource provisioning schemes in Internet services, servers end up less than 50 % utilized almost all the time. At this level of utilization, the servers ’ energy efficiency is less than half their efficiency at peak utilization. A solution to this problem could be consolidating workloads into fewer servers and turning others off. However, services typically resist doing so. A major reason is the fear of slow response times during re-activation in handling traffic spikes. Another reason is that services want to maximize the amount of main memory available for data caching across the server cluster. In this paper, we propose an approach that does not completely shutdown idle servers and allows free memory space to be used for cooperative data caching. Specifically, we make two key contributions. First, we propose to send servers to a new “barely-alive ” power state, instead of turning them off after consolidation. Our barely-alive servers allow remote accesses to their main memories even when all processing cores have been turned off. Second, we design a distributed middleware that accommodates barely-alive servers and is capable of dynamically re-sizing the amount of cache space across the cluster to the minimum required to respect the service’s service-level agreement (SLA). Any memory that is not in use by the middleware can be used by applications. Our trace-driven simulations of a server cluster using our middleware and barely-alive servers show very encouraging results. 1.
A Barely Alive Memory Servers: Keeping Data Active in a Low-Power State
"... Current resource provisioning schemes in Internet services leave servers less than 50 % utilized almost all the time. At this level of utilization, the servers ’ energy efficiency is substantially lower than at peak utilization. A solution to this problem could be dynamically consolidating workloads ..."
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Cited by 5 (0 self)
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Current resource provisioning schemes in Internet services leave servers less than 50 % utilized almost all the time. At this level of utilization, the servers ’ energy efficiency is substantially lower than at peak utilization. A solution to this problem could be dynamically consolidating workloads into fewer servers and turning others off. However, services typically resist doing so, because of high response times during reactivation in handlingtraffic spikes. Moreover, services often want the memory and/or storage of all servers to be readily available at all times. In this paper, we propose a family of barely-alive active low-power server states that facilitates both fast re-activation and access to memory while in a low-power state. We compare these states to previously proposed active andidle states.In particular, we investigatethe impact of load burstsin eachenergy-saving scheme.We also evaluate the additional benefits of memory access under low-power states witha studyof a searchservice usingacooperative main-memorycache.Finally,wepropose asystemthatcombinesabarelyalive state with the off state. We find that the barely-alive states can reduce service energy consumption by up to 38%, compared to an energy-oblivious system. We also find that these energy savings are consistent across a large parameter space.
A PROactive Request Distribution (PRORD) Using Web Log Mining in a Cluster-Based Web Server
- in Proceedings of the International Conference on Parallel Processing (ICPP’06
, 2006
"... ABSTRACT ..."
Power-aware Resource Allocation for CPU- and Memory-intense Internet Services
"... Abstract. Internet service providers face the daunting task of maintain-ing guaranteed latency requirements while reducing power requirements. In this work, we focus on a class of services with very high cpu and memory demands, best represented by internet search. These services provide strict laten ..."
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Abstract. Internet service providers face the daunting task of maintain-ing guaranteed latency requirements while reducing power requirements. In this work, we focus on a class of services with very high cpu and memory demands, best represented by internet search. These services provide strict latency guarantees defined in Service-Level Agreements, yet the clusters need to be flexible to different optimizations, i.e. to min-imize power consumption or to maximize resource usage. Unfortunately, standard cluster algorithms, such as resource allocation, are oblivious of the SLA allocations, while power management is typically only driven by cpu demand. We propose a power-aware resource allocation algorithm for the cpu and the memory which is driven by SLA and allows for various dynamic cluster configurations, from energy-optimal to resource-usage-optimal. Using trace-based simulation of two service models, we show that up to 24 % energy can be preserved compared to the state-of-art scheme, or maximum memory utility can be achieved with 20 % savings.
Exploiting Phase-Change Memory in Cooperative Caches
"... Modern servers require large main memories, which so far have been enabled by improvements in DRAM density. However, the scalability of DRAM is approaching its limit, so Phase-Change Memory (PCM) is being considered as an alternative technology. PCM is denser, more scalable, and consumes lower idle ..."
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Modern servers require large main memories, which so far have been enabled by improvements in DRAM density. However, the scalability of DRAM is approaching its limit, so Phase-Change Memory (PCM) is being considered as an alternative technology. PCM is denser, more scalable, and consumes lower idle power than DRAM, while exhibiting byte-addressability and access times in the nanosecond range. Unfortunately, PCM is also slower than DRAM and has limited endurance. These characteristics prompted the study of hybrid memory systems, combining a small amount of DRAM and a large amount of PCM. In this paper, we leverage hybrid memories to improve the performance of cooperative memory caches in server clusters. Our approach entails a novel policy that exploits popularity information in placing objects across servers and memory technologies. Our results show that (1) DRAM-only and PCM-only memory systems do not perform well in all cases; and (2) when managed properly, hybrid memories always exhibit the best or close-to-best performance, with significant gains in many cases, without increasing energy consumption. Keywords-Cooperative memory caches; persistent memory. I.
Exploiting Phase-Change Technology in Server Memory Systems
, 2012
"... Main memory capacity is becoming a critical issue for modern server systems. Unfortunately, current trends suggest that meeting these capacity requirements using DRAM will not be ideal. DRAM consumes significant amounts of energy (idle, refresh, and precharge energies) and will soon reach its densit ..."
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Main memory capacity is becoming a critical issue for modern server systems. Unfortunately, current trends suggest that meeting these capacity requirements using DRAM will not be ideal. DRAM consumes significant amounts of energy (idle, refresh, and precharge energies) and will soon reach its density limit. Many researchers in industry and academia point to Phase-Change Memory (PCM) technology as a promising replacement for DRAM. PCM is byte-addressable as DRAM, but presents higher density and lower idle power consumption than DRAM. However, PCM is also slower than DRAM and has limited endurance. For these reasons, hybrid memory systems that combine a small amount of DRAM and a large amount of PCM have become attractive. In this dissertation, we propose two hybrid memory systems for servers. The first system (called Rank-aware Page Placement or RaPP) is a hardware-driven page placement policy. The policy relies on the memory controller (MC) to monitor access patterns, migrate pages between DRAM and PCM, and translate the memory addresses coming from the cores. The second system (called Rank-aware Cooperative Cache or
Exploiting Phase-Change Memory in Cooperative Caches
"... Modern servers require large main memories, which so far have been enabled by improvements in DRAM density. However, the scalability of DRAM is approaching its limit, so Phase-Change Memory (PCM) is being considered as an alternative technology. PCM is denser, more scalable, and consumes lower idle ..."
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Modern servers require large main memories, which so far have been enabled by improvements in DRAM density. However, the scalability of DRAM is approaching its limit, so Phase-Change Memory (PCM) is being considered as an alternative technology. PCM is denser, more scalable, and consumes lower idle power than DRAM, while exhibiting byte-addressability and access times in the nanosecond range. Unfortunately, PCM is also slower than DRAM and has limited endurance. These characteristics prompted the study of hybrid memory systems, combining a small amount of DRAM and a large amount of PCM. In this paper, we leverage hybrid memories to improve the performance of cooperative memory caches in server clusters. Our approach entails a novel policy that exploits popularity information in placing objects across servers and memory technologies. Our results show that (1) DRAM-only and PCM-only memory systems do not perform well in all cases; and (2) when managed properly, hybrid memories always exhibit the best or close-to-best performance, with significant gains in many cases, without increasing energy consumption. Keywords-Cooperative memory caches; persistent memory. I.
Barely Alive Servers: Greener Datacenters Through Memory-Accessible, Low-Power States
"... Abstract Current resource provisioning schemes in Internet services leave servers less than 50 % utilized almost all the time. At this level of utilization, the servers’ energy efficiency is substantially lower than at peak utilization. A solution to this problem could be dynamically consolidating w ..."
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Abstract Current resource provisioning schemes in Internet services leave servers less than 50 % utilized almost all the time. At this level of utilization, the servers’ energy efficiency is substantially lower than at peak utilization. A solution to this problem could be dynamically consolidating workloads into fewer servers and turning others off. However, services typically resist doing so, because of high response times during re-activation in handling traffic spikes. Moreover, services often want the memory and/or storage of all servers to be readily available at all times. In this paper, we propose a family of barely-alive active low-power server states that facilitates both fast re-activation and access to memory while in a low-power state. We compare these states to previously proposed active and idle states. In particular, we investigate the impact of load bursts in each energy-saving scheme. We also evaluate the additional benefits of memory access under low-power states with a study of a search service using a cooperative main-memory cache. Finally, we further investigate our barely-alive states in two case studies: (1) a mixed system that combines a barely-alive state with the off state to maximize energy savings; and (2)
G IH Network and Grid Support for Multimedia Distribution and Processing
"... I would like to express my gratefulness to prof. Luděk Matyska and dr. Eva Hladká for supporting me in my work a motivating me. I would also like to thank the fellows at the Laboratory of Advances Networking Technologies: Lukáš Hejtmánek, Tomáš Rebok, Miloš Liška, Jiˇrí Denemark, and others for crea ..."
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I would like to express my gratefulness to prof. Luděk Matyska and dr. Eva Hladká for supporting me in my work a motivating me. I would also like to thank the fellows at the Laboratory of Advances Networking Technologies: Lukáš Hejtmánek, Tomáš Rebok, Miloš Liška, Jiˇrí Denemark, and others for creating a great team which I really appreciate to work with. Furthermore, I’d like to thank my parents and my grandparents and especially my grandfather Miloslav, who spent huge amount of time with me and being an excellent professor. He has taught me how to love languages and mathematics and how these fields are closely interrelated. And last but not least, I’d like to appreciate my wife Aleška, who has been helping me immensely in the recent years and soothing and encouraging me in the moments when I was feeling really down. In this thesis, we focus our work on two classes of multimedia data distribution and processing problems: synchronous or interactive, which require as low latency as possible, and asynchronous or non-interactive, where latency is not so restrictive.
Distributed Active Element in 10 Gbps Network
"... Abstract—In this paper, we propose a distributed Active Element for tightly coupled cluster environment, suitable for distribution of large bandwidth data that exceed capacity of every single node in the cluster. This approach utilizes the fact that real-time multimedia transmission systems relying ..."
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Abstract—In this paper, we propose a distributed Active Element for tightly coupled cluster environment, suitable for distribution of large bandwidth data that exceed capacity of every single node in the cluster. This approach utilizes the fact that real-time multimedia transmission systems relying on nonguaranteed protocols like UDP need to handle limited packet reordering on their own. We describe the Fast Circulating Token protocol, which enables imposing even stricter bound on the outbound packet reordering. The whole system is examined on 10GE testbed and shows very good performance. The FCT provides expected improvement, making the packet reordering comparable to long haul networks. Index Terms—multi-point user-empowered data distribution, distributed Active Elements, virtual multicast, multimedia data distribution I.
