{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/44101"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/44101","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Software systems for power and energy conservation","abstract":"The continued scaling of transistors in accordance with Moore's law and the failure of Dennard scaling has resulted in power becoming a critical factor in all facets of microprocessor design. To counter the Power Wall, techniques such as voltage and frequency scaling, heterogeneous hardware and voltage underscaling coupled with improved application reliability have been proposed. Most of the innovation for power conservation has happened at the hardware level. Software needs to be equally responsible for power conservation. For instance, mobile cloud computing is used to offload compute intensive tasks that affect a mobile device's battery. Mobile ad-hoc computing can be used as an alternative to mobile cloud computing in cases where cloud access is not available or is inhibitive to application performance. This thesis presents two systems - Synergy and Equilibria which aid the hardware in its pursuit of conserving power. Synergy is a middleware that increases the battery life for a system of mobile devices connected in a peer-to-peer ad-hoc network. Synergy conserves energy by scaling core frequencies and by intelligently distributing the computation among peer devices. The middleware is not restricted to mobile phones and in no way restricts the mobility of the devices. Equilibria provides software support for voltage domains connected in series. Hardware innovations for power conservation have ignored the power losses incurred by the power delivery circuits in face of low voltage and high current demands. Connecting the voltage domains in a series circuit (instead of parallel) can result in highly efficient power delivery. For series connected voltage domains to work, the voltage draw by each load should be the same. This voltage drop (across the load) is dependent on its CPU utilization. Equilibria is a load balancer which actively monitors the CPU utilization of the processors in the system and ensures equal voltage draw. It runs on a master processor and alters the frequency of the client processors based on the average CPU utilization of all the processors in the system. Equilibria is generic, i.e. the system works irrespective of the software running on the processors.","abstract_html":"The continued scaling of transistors in accordance with Moore's law and the failure of Dennard scaling has resulted in power becoming a critical factor in all facets of microprocessor design. To counter the Power Wall, techniques such as voltage and frequency scaling, heterogeneous hardware and voltage underscaling coupled with improved application reliability have been proposed. Most of the innovation for power conservation has happened at the hardware level. Software needs to be equally responsible for power conservation. For instance, mobile cloud computing is used to offload compute intensive tasks that affect a mobile device's battery. Mobile ad-hoc computing can be used as an alternative to mobile cloud computing in cases where cloud access is not available or is inhibitive to application performance. This thesis presents two systems - Synergy and Equilibria which aid the hardware in its pursuit of conserving power. Synergy is a middleware that increases the battery life for a system of mobile devices connected in a peer-to-peer ad-hoc network. Synergy conserves energy by scaling core frequencies and by intelligently distributing the computation among peer devices. The middleware is not restricted to mobile phones and in no way restricts the mobility of the devices. Equilibria provides software support for voltage domains connected in series. Hardware innovations for power conservation have ignored the power losses incurred by the power delivery circuits in face of low voltage and high current demands. Connecting the voltage domains in a series circuit (instead of parallel) can result in highly efficient power delivery. For series connected voltage domains to work, the voltage draw by each load should be the same. This voltage drop (across the load) is dependent on its CPU utilization. Equilibria is a load balancer which actively monitors the CPU utilization of the processors in the system and ensures equal voltage draw. It runs on a master processor and alters the frequency of the client processors based on the average CPU utilization of all the processors in the system. Equilibria is generic, i.e. the system works irrespective of the software running on the processors.","abstract_has_math":false,"creators":["Kharbanda, Harshit"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Campbell, Roy H."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-05-24T21:50:45Z","date_published":"2013-05-24T21:50:45Z","updated_at":"2026-07-22T22:25:33Z","subjects":["power","energy","mobile","synergy","power delivery","power delivery losses","series circuit","parallel circuit","operating system","middleware","load balancer","software for power","software for energy","Hardware","architecture","OpenCV","image","video","Peer to peer (P2P)","peer-to-peer","Raspberry Pi","Raspberry","Raspi","voltage regulator","frequency governor","ondemand","Linux","alljoyn","powertutor","wifi","Wi-Fi"],"languages":["en"],"rights":["Copyright 2013 Harshit Kharbanda"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/44101","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Campbell, Roy H."]},{"key":"dc:creator","label":"Author","values":["Kharbanda, Harshit"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2013-05-24T21:50:45Z","2013-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["power","energy","mobile","synergy","power delivery","power delivery losses","series circuit","parallel circuit","operating system","middleware","load balancer","software for power","software for energy","Hardware","architecture","OpenCV","image","video","Peer to peer (P2P)","peer-to-peer","Raspberry Pi","Raspberry","Raspi","voltage regulator","frequency governor","ondemand","Linux","alljoyn","powertutor","wifi","Wi-Fi"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2013 Harshit Kharbanda"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/44101"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The continued scaling of transistors in accordance with Moore's law and the failure of Dennard scaling has resulted in power becoming a critical factor in all facets of microprocessor design. To counter the Power Wall, techniques such as voltage and frequency scaling, heterogeneous hardware and voltage underscaling coupled with improved application reliability have been proposed. Most of the innovation for power conservation has happened at the hardware level. Software needs to be equally responsible for power conservation. For instance, mobile cloud computing is used to offload compute intensive tasks that affect a mobile device's battery. Mobile ad-hoc computing can be used as an alternative to mobile cloud computing in cases where cloud access is not available or is inhibitive to application performance. This thesis presents two systems - Synergy and Equilibria which aid the hardware in its pursuit of conserving power. Synergy is a middleware that increases the battery life for a system of mobile devices connected in a peer-to-peer ad-hoc network. Synergy conserves energy by scaling core frequencies and by intelligently distributing the computation among peer devices. The middleware is not restricted to mobile phones and in no way restricts the mobility of the devices. Equilibria provides software support for voltage domains connected in series. Hardware innovations for power conservation have ignored the power losses incurred by the power delivery circuits in face of low voltage and high current demands. Connecting the voltage domains in a series circuit (instead of parallel) can result in highly efficient power delivery. For series connected voltage domains to work, the voltage draw by each load should be the same. This voltage drop (across the load) is dependent on its CPU utilization. Equilibria is a load balancer which actively monitors the CPU utilization of the processors in the system and ensures equal voltage draw. It runs on a master processor and alters the frequency of the client processors based on the average CPU utilization of all the processors in the system. 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To counter the Power Wall, techniques such as voltage and frequency scaling, heterogeneous hardware and voltage underscaling coupled with improved application reliability have been proposed. Most of the innovation for power conservation has happened at the hardware level. Software needs to be equally responsible for power conservation. For instance, mobile cloud computing is used to offload compute intensive tasks that affect a mobile device's battery. Mobile ad-hoc computing can be used as an alternative to mobile cloud computing in cases where cloud access is not available or is inhibitive to application performance. This thesis presents two systems - Synergy and Equilibria which aid the hardware in its pursuit of conserving power. Synergy is a middleware that increases the battery life for a system of mobile devices connected in a peer-to-peer ad-hoc network. Synergy conserves energy by scaling core frequencies and by intelligently distributing the computation among peer devices. The middleware is not restricted to mobile phones and in no way restricts the mobility of the devices. Equilibria provides software support for voltage domains connected in series. Hardware innovations for power conservation have ignored the power losses incurred by the power delivery circuits in face of low voltage and high current demands. Connecting the voltage domains in a series circuit (instead of parallel) can result in highly efficient power delivery. For series connected voltage domains to work, the voltage draw by each load should be the same. This voltage drop (across the load) is dependent on its CPU utilization. Equilibria is a load balancer which actively monitors the CPU utilization of the processors in the system and ensures equal voltage draw. It runs on a master processor and alters the frequency of the client processors based on the average CPU utilization of all the processors in the system. Equilibria is generic, i.e. the system works irrespective of the software running on the processors.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2013-04-11T19:26:54Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 49 StackedLoadsExample.pdf: 24157 bytes, checksum: 34685b32048eb0b2a491af1352160b4a (MD5) StackedLoads4.pdf: 24312 bytes, checksum: 784a7e9cc8a1034e02811cdcee301eb5 (MD5) SoCSchematic.pdf: 22006 bytes, checksum: 57869454669e5d7a9aa7027e3f78fe37 (MD5) raspi_freqvspower_ratio.pdf: 7486 bytes, checksum: 042b6a1726db8b411750b45c0c2fee7f (MD5) raspi_freq_scaling_plot_power6.pdf: 7759 bytes, checksum: a38d214a95d1e1cd410d1fa2b52e753e (MD5) power_consumption_3_on.pdf: 10739 bytes, checksum: 34687dbf8d9e7446ca8cf5ddf6d437be (MD5) power_consumption_2_on.pdf: 10020 bytes, checksum: c70144febd76ba35aa7ede8297e02bf5 (MD5) power_consumption_1_on.pdf: 8752 bytes, checksum: 05877c0fc1455f3d7a358cd240e84615 (MD5) ParallelLoads4.pdf: 22710 bytes, checksum: 7d8839f4c130828d0606fb9b6216aab0 (MD5) MasterFlowchart.pdf: 360849 bytes, checksum: edb23f0c7e7b9ee2d4e889e295c577fb (MD5) LatencyVsEnergy.pdf: 8576 bytes, checksum: db3970c2047040bbea82676613852fa0 (MD5) Latency50MB.pdf: 7002 bytes, checksum: 2f511a29942aa950a50f572634558f30 (MD5) Latency25MB.pdf: 7286 bytes, checksum: b5b72c5842571c481c6c4d3a8a09eb76 (MD5) Latency6MB.pdf: 7181 bytes, checksum: 9443f10abe2271bc160bde6e4ad9a863 (MD5) Latency4MB.pdf: 6930 bytes, checksum: 27a5760a00b3a9602d75e565ba37c74b (MD5) Latency2MB.pdf: 6746 bytes, checksum: da00a6b2e24f8434bb8210a46452a676 (MD5) ITRS.pdf: 81016 bytes, checksum: 17f680b31476e61b71b87d62a05ffd08 (MD5) EnergySplitup50MB.pdf: 24716 bytes, checksum: c2d95eff1ed5a94df626b15b4d30bb37 (MD5) EnergySplitup25MB.pdf: 24925 bytes, checksum: 626eabdd791588f1bbcfc64057830b38 (MD5) EnergySplitup6MB.pdf: 25585 bytes, checksum: 2b8c73f624c1eb986599ecc2b1eff4dd (MD5) EnergySplitup4MB.pdf: 26804 bytes, checksum: 8cf4159bf1706a271d175eb0d85fcb3a (MD5) EnergySplitup2MB.pdf: 25061 bytes, checksum: 6d5689ff812cfe396a259769047bda64 (MD5) Energy_Consumption_Vs_Number_of_devices.pdf: 7826 bytes, checksum: 2efb502610b06305628f2db1e9c8b821 (MD5) Energy50MB.pdf: 7601 bytes, checksum: 23ed0bbca141a25e01a0a053a381429d (MD5) Energy25MB.pdf: 7436 bytes, checksum: 85cf89110858b309f4c0d5cedd076511 (MD5) Energy6MB.pdf: 7355 bytes, checksum: 90e9be0ec61570a7c482b0403e64fffe (MD5) Energy4MB.pdf: 7632 bytes, checksum: ffc07c9748e78cfe02dbdea4c2f66553 (MD5) Energy2MB.pdf: 7363 bytes, checksum: e969fc824cb0e293a8a62800f5dd4dea (MD5) Communication_Latency_Vs_Number_of_devices.pdf: 7594 bytes, checksum: 7cfa6e4cbb1a4a3fbc953183154084a2 (MD5) ClientFlowchart.pdf: 607051 bytes, checksum: 2fc91a5affc8f62a4d51048fa164a4d1 (MD5) system_components.tex: 4364 bytes, checksum: dab9112c9173f47ff8340b75dbc4fbee (MD5) synergy_design.tex: 12152 bytes, checksum: ce0278868d18400e351ccfb0aef268e7 (MD5) synergy_algorithm.tex: 1581 bytes, checksum: 47469e825c1cf06e94405961f5deda8a (MD5) series_connected_domains_basic.tex: 3145 bytes, checksum: a52ffc3fea0fc428d4df4da7c73e4196 (MD5) results.tex: 11242 bytes, checksum: 10bf2894b373bbe928df643631724247 (MD5) mybib.bib: 22472 bytes, checksum: 1e7f77212c9b38f9b0511db0c3fe8732 (MD5) mobile_savings.tex: 6557 bytes, checksum: 9f77fd31532cc1eb3782c2abcd0c4ffb (MD5) limitations.tex: 3556 bytes, checksum: d3b2273b6638c7875aa8b88709ba48bb (MD5) intro.tex: 7366 bytes, checksum: 344bc936816b19a12a5dcbadb2b4b0a6 (MD5) Evaluation.tex: 288 bytes, checksum: 825ed6213e9de068130d07ecf905ba45 (MD5) dedication.tex: 139 bytes, checksum: 94d4913eac7b46c8f5e7d374933b048a (MD5) datacenter_savings.tex: 770 bytes, checksum: fd6cd3c0fb6bb2dc9622d3bdfa5ac786 (MD5) datacenter_design.tex: 4286 bytes, checksum: e93828d3659f95056120bf0370247a1e (MD5) conclusion.tex: 1775 bytes, checksum: bdaf70d3648b024357071becee64a7d4 (MD5) background.tex: 4514 bytes, checksum: 465c75918ee539b62f6dd389368a6de3 (MD5) ack.tex: 1028 bytes, checksum: 014472979b2a5a2811dfcd85a83d7fcf (MD5) abstract.tex: 2224 bytes, checksum: 6ddc78ea119930012309c1115bd58b8d (MD5) thesis.tex: 2798 bytes, checksum: 2c36ad2e08383eedfc1ea7962b706196 (MD5) Kharbanda_Harshit.pdf: 1703154 bytes, checksum: fe34202339be206e8b9b7afe185d4891 (MD5)","Made available in DSpace on 2013-05-24T21:50:45Z (GMT). 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