Search Results for "high performance computing" - Page 4
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Showing 99 open source projects for "high performance computing"
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Strategems
Quantitative systematic trading strategy development and backtesting
...This package is inspired in large part by the quantstrat1,2 package in R, adopting a similar general structure to the building blocks that make up a strategy. Given the highly iterative nature of event-driven trading strategy development, Julia's high-performance design (particularly in the context of loops) and straightforward syntax would seem to make it a natural fit as a language for systematic strategy research and development. While this package remains early in development, with time the hope is to be able to rapidly implement a trading idea, construct a historical backtest, analyze its results, optimize over a given parameter set, and visualize all of this with great detail. -
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DSPatch
The Refreshingly Simple C++ Dataflow Framework
Webite: http://flowbasedprogramming.com DSPatch, pronounced "dispatch", is a powerful C++ dataflow framework. DSPatch is not limited to any particular domain or data type, from reactive programming to stream processing, DSPatch's generic, object-oriented API allows you to create virtually any dataflow system imaginable. *See also:* DSPatcher ( https://github.com/MarcusTomlinson/DSPatcher ): A cross-platform graphical tool for building DSPatch circuits. DSPatchables (... -
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inMap
Rich layers, better user experience, big data geographic visualization
inMap is a big data visualization library based on Baidu Map. It focuses on the display of scatter, heat map, grid, and aggregation in the direction of big data. It is committed to making big data visualization easy to use. -
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OpenFace
A state-of-the-art facial behavior analysis toolkit
...OpenFace is available for Windows, Ubuntu and macOS installations. It is capable of real-time performance and does not need to run on any specialist hardware, a simple webcam will suffice. -
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Wally
Distributed Stream Processing
...Wally makes it easy to react to data in real-time. By eliminating infrastructure complexity, going from prototype to production has never been simpler. When we set out to build Wally, we had several high-level goals in mind. Create a dependable and resilient distributed computing framework. Take care of the complexities of distributed computing "plumbing," allowing developers to focus on their business logic. Provide high-performance & low-latency data processing. Be portable and deploy easily (i.e., run on-prem or any cloud). Manage in-memory state for the application. ... -
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Central Proteomics Facilities Pipeline
A data analysis pipeline for shotgun mass-spectrometry proteomics.
...However: * Limited fixes have been made on the main master branch by Phil Charles at the University of Oxford. * As of 2019, limited maintenance is being carried out by myself (now in the BioHPC high performance computing group at UTSW), to allow CPFP to install and run on RHEL 7 / CentOS 7, with updated TPP 5.1.0 and search tools. This updated code can be found in the utsw-biohpc branch of the git repository, and may become a 2.2.0 release if time and testing allows. -- David Trudgian - 2019/01/03 -
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X10
Performance and Productivity at Scale
X10 is a class-based, strongly-typed, garbage-collected, object-oriented language. To support concurrency and distribution, X10 uses the Asynchronous Partitioned Global Address Space programming model (APGAS). This model introduces two key concepts -- places and asynchronous tasks -- and a few mechanisms for coordination. With these, APGAS can express both regular and irregular parallelism, message-passing-style and active-message-style computations, fork-join and bulk-synchronous... -
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Vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python
Data science solutions, insights, dashboards, machine learning, deployment. We start at 100GB. Vaex is a high-performance Python library for lazy Out-of-Core data frames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion (10^9) samples/rows per second. Visualization is done using histograms, density plots and 3d volume rendering, allowing interactive exploration of big data. ... -
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EZAudio
An iOS and macOS audio visualization framework
...I've designed six audio components and two interface components to allow you to immediately get your hands dirty recording, playing, and visualizing audio data. These components simply plug into each other and build on top of the high-performance, low-latency AudioUnits API and give you an easy to use API written in Objective-C instead of pure C. EZAudio was designed to work transparently across all iOS and OSX devices. This means one universal API whether you're building for Mac or iOS. For instance, under the hood an EZAudioPlot knows that it will subclass a UIView for iOS or an NSView for OSX and the EZMicrophone knows to build on top of the RemoteIO AudioUnit for iOS, but defaults to the system defaults for input and output for OSX. -
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ParallelAccelerator.jl
ParallelAccelerator package, part of the High Performance Scripting
...It also parallelizes and vectorizes many data-parallel operations. ParallelAccelerator is part of the High Performance Scripting (HPS) project at Intel Labs. -
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circlize
Circular visualization in R
...It implements many types of plots using circular layouts: chord diagrams, circular heatmaps, arcs/links between sectors, genomic data visualization, etc. It provides low-level drawing functions as well as high-level functions to build complex visualizations. It’s often used in genomics, network analysis, or other fields where relationships among categories or entities can be nicely displayed in a circular fashion. Support for circular heatmaps, multiple tracks (rings), for showing multiple layers of data per sector. Good performance and stable codebase, detailed documentation including a book on usage examples. -
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PROPER is a package for visual evaluation of ranking classifiers for biological big data mining studies in the mathematical language MATLAB. It is an efficient tool for optimization and comparison of the state-of-the-art ranking classifiers by generating over 20 different high quality two- and three-dimensional performance curves.
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Apache Kafka
Mirror of Apache Kafka
Apache Kafka is a distributed streaming platform built around durable, partitioned logs called topics, enabling high-throughput, fault-tolerant event pipelines. Producers append records to partitions, brokers replicate them for durability, and consumer groups read them at their own pace while balancing work across instances. The commit/offset model and retention policies support patterns from real-time processing to event sourcing and audit trails. Exactly-once processing semantics,... -
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PROPER is a package for visual evaluation of ranking classifiers for biological big data mining studies in the mathematical language MATLAB. It is an efficient tool for optimization and comparison of the state-of-the-art ranking classifiers by generating over 20 different high quality two- and three-dimensional performance curves.
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FlowVR is an open source middleware tailored for high performance in situ data processing and analytics running on large parallel machines
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Open-source, cross-platform 3D rendering engine for .NET and Mono. The Axiom Engine is a high-performance C# port of the powerful OGRE engine and provides full support for DirectX, OpenGL and XNA on Windows, Linux, Android, iPhone and Windows Phone.
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MapReduce Brazil
Aggregates MapReduce projects
Nowadays the production and storage of Big Data is common, both in the academy and in the enterprises. To process this huge amount of data it is essential the use of high performance platforms and programming models like MapReduce -
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Cca-forum unifies the Common Component Architecture tools and tutorial. It includes the CCA specifications, the Ccaffeine framework for HPC, and related tools. These support multilanguage scientific and parallel computing.
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QuickFlash is a C++-based analysis library for data files generated by the Flash hydrodynamics code. It provides high-performance access to large datasets in low memory situations and other restrictive environments.
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Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming
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An open source data version repository model based on true INSERT only logic. Contains high performance support for data versioning and history. Enables point-in-time query and CDC sourcing including mapping each change to a transaction.
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HCI for audiovisual live performance exploiting physical computing. Transform your standard musical instrument - electric bass, guitar, violin, piano etc - in an augmented tool, an audiovideo controller without exploiting any specific ext. hardware.
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PyVisi is the Python visualisation interface: a generic Python-based interface to many different scientific visualisation packages. PyVisi is intended for use in both standard and high-performance computing environments, and with the escript package.
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pySPACE
Signal Processing and Classification Environment in Python using YAML
pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due...
