Case Study: Sleepmed

Aaron Taylor Case Studies Leave a Comment

Sleepmed is a biomedical company that focuses on improving the health and quality of life of those who suffer from sleep disorders. Sleepmed is the nation’s leader in sleep diagnosis and provides services to more than 80,000 patients annually in one of their 200 labs located in 32 states across the USA. To accomplish this task they created hardware that automatically collects a few gigabytes of important diagnostic data on patients when they sleep. These data are automatically reduced and processed to reveal important events which are later interpreted by sleep specialists. Mission SleepMed was in the process of developing new data collection hardware which, in principle, could share a significant fraction of the code base with the existing hardware. …

Case Study: Reveal Imaging

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Iterative reconstruction from projections is typically a function reserved for the medical industry. This approach allows medical professionals to reconstruct computed tomography (CT) images from acquired data; the reconstructed images display virtual “slices” of a scanned object, such as a heart or brain. In reconstructing an image from the data, algorithms are used to approximate the solution. The closer the solution, the better the reconstruction. Multiple iterations produce more accurate solutions, and, thus, higher-quality images. This technique, however, consumes computation time; speeding the process through the GPU is one solution to this problem. Mission Reveal Imaging, a SAIC company, uses this CT technology in developing threat-detection products for transportation systems—such as cargo and baggage screening in airports—and in securing facilities and …

Case Study: 3Dfit App for glasses.com

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Many find the experience of purchasing new glasses stressful. Even simply trying on frames can be uncomfortable when done in a public setting. Glasses.com set out to improve the experience by providing customers a way of virtually trying on glasses frames in the comfort of their homes via smartphone or tablet. The Glasses.com app takes a picture of the user’s face, creates a 3D model of facial features, and virtually places selected frames on the user’s 3D image. The user is then free to view the 3D image from a variety of angles. The application relies on computer vision to recognize the features of a user’s face and then generate an accurate, high-fidelity, 3D model of that face. Virtual frames …

Case Study: A Fortune 200 Insurance Company

Scott Case Studies Leave a Comment

A Fortune 200 Insurance Company located on the West coast was using a third-party, closed-source application to make inferences about future market conditions in order to hedge their investments. In order to carry out calculations over millions of possible scenarios, they were using a small cluster consisting of 1,300 hyperthreaded CPU cores in blade servers. In the near term, they projected that their business needs would grow by a factor of two and they were near capacity with their existing system. Mission The Client hired ArrayFire to conduct a comprehensive audit of their system to access its performance in nine key areas: The technological platform – a high-level overview of their system, example execution flows, discussions of shortcomings of their …

Whole Brain Dynamics at Single Neuron Resolution

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Empirical Dynamic Modeling (EDM) is a mathematical framework designed for studying nonlinear dynamical systems. EDM is based upon the concept of state-space reconstruction (SSR). Takens’ theorem states that the attractor manifold of a multivariate dynamical system can be reconstructed from time-lagged coordinates of a single time series variable. Figure 1 illustrates the concept of state space reconstruction. EDM encompasses multiple functions, but we focused on two main techniques, the simplex projection, which uses individual variables to create univariate embeddings to predict itself, and convergent cross-mapping (CCM) a method for nonlinear causal inference. Simplex projection is a nonlinear forecasting algorithm often used for estimating the dimensionality of a dynamical system using its prediction skill as a selection criterion. Simplex projection uses …

Finger Vein Identity Recognition in “Negligible Time” using ArrayFire

John Melonakos ArrayFire, Case Studies, Computer Vision, CUDA, Open Source Leave a Comment

In this blog post, we summarize work by researchers in Slovakia using ArrayFire to develop OpenFinger, a finger vein identity recognition library. Finger prints and finger veins can be used as a biometric for identity recognition. The physical setup of their sensor system is the following collection of CMOS sensors scattering light to a near infrared LED that projects the image to a CCD camera for capture to a computer. The computing infrastructure used in this work consists of the following components. Several great open source libraries are used, including OpenCV, Caffe, Qt, and ArrayFire. ArrayFire is specifically used in pre-processing to accelerate Gabor filtering on the GPU. Gabor filter has proven itself as one of the most suitable techniques …

Schrödinger’s Smoke in Unity with ArrayFire

John Melonakos Case Studies Leave a Comment

Researchers in Russia used ArrayFire to achieve impressive results modeling Eulerian incompressible fluids in the Unity game engine. The team developed a solution that allows us to simulate particle systems with high physical accuracy using ArrayFire. The solution makes it possible to simulate the interaction of two vortex rings—their collisions and intersections. The particle system is a method used in computer graphics and interactive simulations to represent objects that do not have clear geometric boundaries. This makes it possible to create practically any type of natural effects—e.g., explosions, jets of steam, nebulae, rain, snow, water splashes, fire smoke, etc. The particle system controls groups of particles—that is, small flat images or mesh objects. Any particle has a certain ‘lifetime’ (usually …

Thrombotherm: Analyzing Blood Platelets with ArrayFire

John Melonakos ArrayFire, Case Studies, Image Processing Leave a Comment

The Thrombotherm project by Catalysts is developing a method to analyze blood platelets by means of cell microscopy in real time and to classify them according to their activation state. ArrayFire enabled faster overall research project times and real-time analysis on video data. This project represents an enormous extension of thrombocyte diagnotics, especially through significantly accelerated analysis times. Faster analyses enabled university research collaborators from the University of Applied Sciences OÖ and the Ludwig Boltzmann Institute to shorten research project times. The project has three main parts: Detect cell morphology in real-time Thombotherm makes it possible to mathematically determine and categorize the cell boundaries by means of transmitted light microscopy. The software distinguishes between “fried-egg”-shaped cells and “spider”-shaped cells. This is used …

Performance of ArrayFire JIT Code Generation

Oded Green Benchmarks, Case Studies 3 Comments

The ArrayFire library offers JIT (Just In Time) compiling for standard arithmetic operations. This includes trigonometric functions, comparisons, and element-wise operations. At run-time, ArrayFire aggregates these function calls using an Abstract Syntax Tree (AST) data structure such that whenever a JIT-supported function is ”met,” it is added into the AST for a given variable instance. The AST of the variable is computed if one of the following conditions is met: When the above occurs, and the variable needs to be evaluated, the functions and variables in the AST data structure are used to create a single kernel (”function-call”). This is done by creating a customized kernel on-the-fly that is made up of all the functions in the AST – the …

Beamforming with ArrayFire

Scott ArrayFire, Case Studies, CUDA Leave a Comment

Alessandro Savoia and researchers at Università degli Studi Roma Tre have achieved an order of magnitude improvement in the performance of a beamforming application using ArrayFire for GPU acceleration with CUDA-capable NVIDIA GPUs. This application involves conventional beamforming. Steps include the application of a time delay to each signal vector, summation across all vectors, and processing on the result. Processing includes demodulation, envelope extraction, and logarithmic compression. ArrayFire’s functions for shifting, interpolation, and filtering made this application possible for acceleration on GPUs and reduced the time to develop significantly. Alessandro’s benchmarks show that a CPU-only version was only running at 1 frame/sec, while the ArrayFire-accelerated version was running at 10-20 frames/sec, depending on the dataset. Alessandro and his team are looking forward to …