Jikes RVM (Research Virtual Machine) provides a flexible open testbed to prototype virtual machine technologies and experiment with a large variety of design alternatives. Jikes RVM runs on many platforms and advances the state-of-the-art of virtual machine technologies for dynamic compilation, adaptive optimization, garbage collection, thread scheduling, and synchronization. It is self-hosted, i.e. its Java code runs on itself without requiring a second virtual machine. Most other virtual machines for the Java platform are written in native code (typically C or C++). A Java implementation provides ease of portability and a seamless integration of virtual machine and application resources such as objects, threads, and operating-system interfaces.
ResearchMaster is a tool that you can trust to help with organization, multitasking, and research, both personal and professional. It provides a place to capture your fleeting thoughts and ideas, and it allows you to hit the ground running on projects. It was developed with professional scientific research in mind, but it's great for grocery lists and address books as well.
LabKey Server is open source software that helps scientists manage, analyze, and share complex datasets. It supports tandem mass spectrometry, flow cytometry, assays for neutralizing antibodies, Luminex, observational studies, and secure, Web-based collaboration. The software is modular, configurable, and customizable. It can be installed in your institution on any modern hardware and operating system. It is designed to integrate with your existing systems, instruments, and work flows, and to be readily adapted by skilled programmers to novel methods of inquiry. The project is under active development by a team of professional software engineers and a community of active contributors. New versions are released about four times per year.
Gerbil consists of an interactive visualization tool targeted at multispectral and hyperspectral image data, and a toolbox of common algorithms, e.g. for segmentation. Multispectral imaging has been gaining popularity and has been gradually applied to many fields besides remote sensing. However, due to the high dimensionality of the data, both human observers and computers have difficulty interpreting this wealth of information. Gerbil facilitates the visualization of the relationship between spectral and topological information in a novel fashion. It puts emphasis on the spectral gradient, which is shown to provide enhanced information for many reflectance analysis tasks. It also includes a rich toolbox for evaluation of image segmentation and other algorithms in the multispectral domain. The parallel coordinates visualization technique is combined with hashing for a highly interactive visual connection between spectral distribution, spectral gradient, and topology.
StarCluster is a utility for creating traditional computing clusters used in research labs or for general distributed computing applications on Amazon's Elastic Compute Cloud (EC2). It uses a simple configuration file provided by the user to request cloud resources from Amazon and to automatically configure them with a queuing system, an NFS shared /home directory, passwordless SSH, OpenMPI, and ~140GB scratch disk space. It consists of a Python library and a simple command line interface to the library. For end-users, the command line interface provides simple intuitive options for getting started with distributed computing on EC2 (i.e. starting/stopping clusters, managing AMIs, etc). For developers, the library wraps the EC2 API to provide a simplified interface for launching/terminating nodes, executing commands on the nodes, copying files to/from the nodes, etc.
eLabFTW is an electronic laboratory notebook system. Once installed on a server, every member of a lab can write up their experiments, upload files, manage a database of products (antibodies, chemicals, siRNA, papers, or whatever you want). It was created with usability and security in mind, is very easy to use, and has a long list of features specific to research life.
Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Theano features tight integration with numpy, transparent use of a GPU, efficient symbolic differentiation, speed and stability optimizations, dynamic C code generation, and extensive unit-testing and self-verification. Theano has been powering large-scale computationally intensive scientific investigations since 2007. But it is also approachable enough to be used in the classroom (IFT6266 at the University of Montreal).