Climateprediction.net aims to harness the spare CPU cycles of a million individual users' PCs to run a massive ensemble of climate simulations using an up-to-date, full resolution, three dimensional atmosphere-ocean climate model. The project has many similarities with other public-resource high-throughput activities but is distinctive in a number of ways including the complexity of the computa...

Networked services are increasingly in demand as traditional services become web-enabled. These high-throughput services today use a pool of worker threads to service requests in parallel on multiprocessor machines [15, 8]. As businesses streamline practices, these services are often critical (e.g., web services for an online retailer or just-in-time supply chaining), requiring methods to manag...

Paxos is probably the most popular state machine replication protocol. Two optimizations that can greatly improve its performance are batching and pipelining. However, tuning these two optimizations to achieve high-throughput can be challenging, as their effectiveness depends on many parameters like the network latency and bandwidth, the speed of the nodes, and the properties of the application...

For many remote sensing application projects, the quality of the research or the product is heavily dependent upon the quantity of computing cycles available. Middleware is software that connects two or more otherwise separate applications across the Internet or local area networks. In this paper, we present the High Throughput Computing Spatial Information Processing (HIT-SIP) System (Prototyp...

In this paper, we explore the tradeoffs and opportunities in porting a high-throughput Grid computing middleware to a high-performance service oriented environment. We present the limitations of the Grid computing middleware when operating in such a performance sensitive environment and suggest ways of overcoming these limitations. We focus on exploiting the computation and communication hetero...

Existing network benchmark tools suffer from problems such as portability, poor repeatability and inability to perform accurate testing of high-throughput networks. We have built a distributed benchmarking tool which solves many of these problems. ipbench provides an extensible distribution framework and makes minimal demands of the device under test. We have fully implemented a latency test wi...

UNLABELLED READSCAN is a highly scalable parallel program to identify non-host sequences (of potential pathogen origin) and estimate their genome relative abundance in high-throughput sequence datasets. READSCAN accurately classified human and viral sequences on a 20.1 million reads simulated dataset in <27 min using a small Beowulf compute cluster with 16 nodes (Supplementary Material). AVAI...

Unique molecular identifiers (UMIs) show outstanding performance in targeted high-throughput resequencing, being the most promising approach for the accurate identification of rare variants in complex DNA samples. This approach has application in multiple areas, including cancer diagnostics, thus demanding dedicated software and algorithms. Here we introduce MAGERI, a computational pipeline tha...

We live in the era of big data. Biological research is not an exception. Since the appearance of highthroughput screening microscopes biologists can acquire hundreds of thousands of images in a short time. The term high-throughput screening incorporates different components of this big data analysis starting from lab automation through cutting-edge microscopy to image analysis and machine learn...

We develop a strategy to design and evaluate high-entropy alloys (HEAs) for structural use in the transportation and energy industries. We give HEA goal properties for low (≤150 °C), medium (≤450 °C) and high (≥1,100 °C) use temperatures. A systematic design approach uses palettes of elements chosen to meet target properties of each HEA family and gives methods to build HEAs from these palettes...