Predictor@Home: A "Protein Structure Prediction Supercomputer" Based on Public-Resource Computing

Abstract

Predicting the structure of a protein from its amino acid sequence is a complex process the understanding of which

The Effectiveness of Threshold-Based Scheduling Policies in BOINC Projects

“…We show that if worker availability and reliability thresholds are both on either end of the spectrum (i.e., close to 0 or 1), performance is unacceptable, i.e., fewer results are delivered in a given amount of time. 3. We show that BOINC applications have "sweet spots", i.e., worker availability and reliability thresholds that, when used to make scheduling decisions, deliver the largest number of valid results in a given amount of time.…”

“…SimBA models the behavior of a BOINC master, including its different scheduling strategies for distribution of tasks. The simulator is driven by real traces from in-production BOINC projects such as Predictor@Home (P@H) [3] to model the behavior of workers that join, participate in, and leave a project.…”

“…VC projects typically are simulations of phenomena in Nature. Some examples of VC projects are: climateprediction.net [4], which explores how the Earth's climate may change in the next century under a wide range of different scenarios; Predictor@Home [3], which predicts protein structures; and Folding@Home [5], which explores the physical processes of protein folding. The VC paradigm emerged in the mid-1990s with two projects, GIMPS and Distributed.net.…”

Ultra Long Integer Multiplication on GDPS

“…So we can use such kind of idle CPU processing time by activate our own program on the idle client. For example SETI@Home [8], Predictor @ Home [6]...etc, provide for solving huge data analysis problems in a Distributed Environment.…”

Large scale execution of a bioinformatic application on a volunteer grid

“…These range from the search to extraterrestrial intelligence [1] to bioinformatic applications [2]. Those loosely coupled applications behave nicely on such large platforms and the aggregated computing power can be compare to huge supercomputers only available in large computing centers, but at a lower cost.…”