A new system architecture for green enterprise computing
Abstract/Contents
- Abstract
- Computing systems account for at least 13% of the electricity use of office buildings. This translates to about 2% of the electricity consumption of the entire US or the equivalent of the State of New Jersey! As computing becomes pervasive, making these systems more efficient is an opportunity to reduce operational costs and have a positive environmental impact. Unfortunately, current understanding of energy consumption in office buildings is limited and coarse-grained. Without better visibility into how electricity is spent and how much of it is wasted, it is difficult to find ways to reduce it. Powernet -- a multi-year power and utilization study of the computing infrastructure in the Computer Science Department at Stanford University -- begins to address the visibility problem in one building. Powernet's data is collected via a large network of plug-level wireless power meters and software sensors that cover a significant portion of the 2nd, 3rd, and 4th floors of the Gates building at Stanford. The Powernet data show that at least 25% of Gates's electricity is wasted on idle and over-provisioned devices. At the extreme, many desktops operate at near-idle for 75% of the time. The combination of high idle power and low utilization means that a large chunk of energy is wasted. This highlights an opportunity to improve on current computing systems. This dissertation presents a novel system architecture for office computing, Any- ware. To save energy, Anyware leverages two observations. First, an increase in energy use does not translate to the same increase in performance. Second, there is a range of resources one can have for a fixed power budget. Anyware's hybrid design splits workload execution between a local low-power client device and a virtual machine (VM) on a backend server. Applications that benefit from hardware optimizations, such as video and graphics, remain local; other tasks (document and picture editing, PDF viewing, etc.) are offloaded to the server. Anyware reduces the energy cost of computing by 70%--80% because the client has power draw comparable to that of a thin client or a laptop (15 to 20 watts) while the server can host multiple user VMs. Fast I/O, the availability of network resources in a LAN environment, and the increased CPU and memory on the server mean that users can get comparable performance at the fraction of the energy cost. Anyware demonstrates that with a new computing architecture, it is possible to have the best of two worlds: desktop performance at the energy costs of thin clients.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2013 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Kazandjieva, Maria A |
|---|---|
| Associated with | Stanford University, Department of Computer Science. |
| Primary advisor | Levis, Philip |
| Thesis advisor | Levis, Philip |
| Thesis advisor | Kozyrakis, Christoforos, 1974- |
| Thesis advisor | McKeown, Nick |
| Advisor | Kozyrakis, Christoforos, 1974- |
| Advisor | McKeown, Nick |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Maria A. Kazandjieva. |
|---|---|
| Note | Submitted to the Department of Computer Science. |
| Thesis | Ph.D. Stanford University 2013 |
| Location | electronic resource |
Access conditions
- Copyright
- © 2013 by Maria Alexandrova Kazandjieva
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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