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Grid Computing
- 1. GRID COMPUTING Faisal N. Abu-Khzam & Michael A. Langston University of Tennessee
- 66. The Grid Service Cluster
- 81. Behind the Scenes Software and Hardware functions PDFs, Libraries VHDL code Configuration file VHDL programmer Server administrator Software programmer Synthesis Client NetSolve server Request Request results
Notas del editor
- Because network speed is increasing faster than platform speeds. It’s easier to tie platforms together rather than building new platforms.
- On-campus infrastructure, funded by NSF, to mirror technologies and interdisciplinary collaborations .
- Regarded as the basic grid building block. Some are General-purpose and some are special-purpose. GSCs will use the same software infrastructure as is now being deployed on the national Grid, but tuned to take advantage of the highly structured and controlled design of the cluster.
- Because a GSC is built around a single advanced data switch,communication services, such as advanced forms of QoS, can be easily implemented within a GSC even though similar services would be problematic across an advanced network.
- Pilchard is a sardine-like fish. Common to the Mediterranean area.
- If user requests a software version, the NetSolve agent may send the request to any server. But, if the user requests the hardware version, then we know that (as it’s currently configured) the agent will send the request to the Machine Design server. The hardware version has the potential to run several hundred times faster than the software version.
- Langston-Dongarra-Plank-Beck-Eijkhout. A big project underway at Tennessee to incorporate grid security. 1-(entire problem is concealed) 2-corroborate: verify if something is true. Send data out, put cryptography on it and check if you receive the right data. 3- more checkpointing enhances reliability and fault tolerance. (there is much overlap between all of the above. Voting: many processrs and some of them are untrusted. Give all of them the same computation and check the answers. Those that do note have the same as majority are thrown out. Scalability: all of the above are concerned with scalability 9as grids get bigger…)
- 1- What’s the right structure? How should grids be organised? Which strategy is better? Harness looks like it’s not dreally popular but Globus is extremely popular. Is it going to be like cars or like PCs? 2- like Netsove? Where everybody can sign on or ? How do you handle Trojan horses? NetSolve ignores them! Because the code runs on the server machine and is not sent to it. So it can’t be infected. Condor actually passes code. So it’s vulnerable to Trojan horses. 2- How much time does a user get on a machine? How much space? Are there clear priority structures? 3-What’s the right metric? Throughput? Elapsed time? 4- What are you monitoring? They measure how busy and loaded a machine is. So how do you monitor a machine without affecting its performance? 5- This will always be an issue in grid computing.