ArrayFire Quantum Simulator

Edwin Solis ArrayFire, Quantum Computing Leave a Comment

ArrayFire is pleased to announce the release of the first version of the open-source quantum simulator programming library, the ArrayFire Quantum Simulator, AQS for short.  AQS is a C++14 library that provides the functionality to create, manipulate, visualize, and simulate quantum circuits with quick and accurate results. The library is built upon ArrayFire to provide hardware-neutral, fast CPU and GPU computations with a familiar interface. Features Its feature set includes: Fast Statevector calculations of 1000+ gates up to 30 qubits Implementing essential gates (Pauli, Superposition, Rotation, Multiple Control gates, etc.) Support for extending and creating gates Implementation of standard algorithms (QFT, Grover, VQE) Granular control over calculation stages Custom text displayer of created circuits and circuit schematics Integration with ArrayFire, …

Exciting Updates at ArrayFire

John Melonakos Announcements, ArrayFire Leave a Comment

Today, we are pleased to announce that our open-source team has joined Intel to focus on building an open future for accelerated computing with oneAPI. At Intel, we will build towards a vision that flourishes at scale, serves domain professionals worldwide, and participates in the exciting oneAPI ecosystem of open-source technical computing. Read more about this on the Intel blog: ArrayFire Team joins Intel for oneAPI. The ArrayFire open-source project will continue to follow The ArrayFire Mission. It will be governed by its maintainers sponsored by a variety of companies, including Google, Twitter, VoltronData, and now Intel. ArrayFire’s support for CUDA, OpenCL, and x86 will continue unchanged. We are also excited to announce that our consulting and training services team …

Visualizing a Trained Neural Network

John Melonakos ArrayFire, Case Studies Leave a Comment

Researchers from the University Bordeaux credit ArrayFire in a paper published in ICPR 2020’s workshop on Explainable Deep Learning for AI. The paper is titled “Samples Classification Analysis Across DNN Layers with Fractal Curves.” It provides a tool for visualizing where the deep neural network starts to be able to discriminate the classes. Summary Deep neural networks (DNN) are becoming the prominent solution when using machine learning models. However, they suffer from a black-box effect that complicates their inner-workings interpretation and thus the understanding of their successes and failures. Information visualization is one way, among others, to help in their interpretability and hypothesis deduction. This paper presents a novel way to visualize atrained DNN to depict at the same time its architecture …

The Torch By ArrayFire: Q3 GPU Updates

John Melonakos ArrayFire, Newsletter Leave a Comment

News for the accelerated computing community – June 27, 2022 Signup for Newsletter Emails Dear Friends, Welcome to the first newsletter for our ArrayFire community! This newsletter brings together people using and developing ArrayFire and other accelerated computing tools. You are part of this vibrant group that “gathers” together around open source work, including: Domain professionals – people who are experts in their disciplines doing serious heavy-lifting from research to production Machine learning gurus – people who care about the best performance for training and inference Hackers – people who love to contribute highly-optimized down-to-the-metal code You are distinguished professionals in your domains, and we hope to build more opportunities for you to interact with the ArrayFire team and one …

An Exact and Fast Computation of the Discrete Fourier Transform for Polar and Spherical Grid

John Melonakos ArrayFire, Case Studies Leave a Comment

Researchers from the University of Central Florida credit ArrayFire in a paper published in IEEE Transactions on Signal Processing. The paper is titled “An Exact and Fast Computation of Discrete Fourier Transform for Polar and Spherical Grid” and provides the first exact and fast solution to the problem of obtaining discrete Fourier transform for polar and spherical grids. This paper is fully reproducible on Github. Summary Numerous applied problems of two-dimensional (2-D) and 3-D imaging are formulated in the continuous domain. They emphasize obtaining and manipulating the Fourier transform in polar and spherical coordinates. However, translating continuum ideas with discretely sampled data on a Cartesian grid is problematic. There exists no exact and fast solution to the problem of obtaining discrete Fourier …

Accelerated NSGA-2 for Multi-Objective Optimization Problems

John Melonakos ArrayFire, Case Studies Leave a Comment

Researchers from the Catalan Telecommunications Technology Centre in Spain credit ArrayFire in a paper published in the Applied Soft Computing Journal. The paper is titled “A GPU fully vectorized approach to accelerate performance of NSGA-2 based on stochastic non-domination sorting and grid-crowding” and showcases ArrayFire accelerating decision space exploration for multi-objective optimization problems. Summary This work introduces an accelerated implementation of NSGA-2 on a graphics processing unit (GPU) to reduce execution time. Parallelism is achieved at the population level using vectorization. All the algorithm components are run on the device, minimizing communication overhead. New stochastic versions of both non-domination sorting and crowding are introduced in the article. They are designed to be efficiently vectorized on GPU; therefore, the proposed approach is finally …

Topology Optimization with Accessibility Constraint for Multi-Axis Machining

John Melonakos Case Studies, Computer Vision Leave a Comment

Researchers from the Palo Alto Research Center (PARC) credit ArrayFire in a paper published in the Journal of Computer-Aided Design. The paper is titled “Topology Optimization with Accessibility Constraint for Multi-Axis Machining” and showcases ArrayFire accelerating the workload. Summary In this post, a topology optimization (TO) framework is presented to enable the automated design of mechanical components while ensuring the result can be manufactured using multi-axis machining. Although TO improves the part’s performance, the as-designed model is often geometrically too complex to be machined, and the as-manufactured model can significantly vary due to machining constraints that are not accounted for during TO. In other words, many of the optimized design features cannot be accessed by a machine tool without colliding with the …

Autonomous Air Refueling Path Planning for UAVs with ArrayFire

John Melonakos Case Studies Leave a Comment

Researchers from the Aeronautics and Space Technologies Institute of the Turkish Air Force Academy credit ArrayFire in a paper published in the Journal of Intelligent & Robotic Systems. The paper is titled “Sigmoid Limiting Functions and Potential Field Based Autonomous Air Refueling Path Planning for UAVs” and showcases ArrayFire in a real-time application of UAV path planning. Summary This paper builds on previous approaches for autonomous air-refueling (AAR) path planning for Unmanned Aerial Vehicles (UAVs). Deficiencies from previous approaches, like smooth maneuvers in the tanker approach and the boundary functions of the potential zones, have been handled. Furthermore, special pattern parameters are added to the approach which makes it suitable for different kind of UAVs that has variable flight speed and turn …

ArrayFire v3.8.2 Release

Umar Arshad Announcements, ArrayFire Leave a Comment

We are pleased to announce another patch release of the ArrayFire library. This release like all patch releases concentrates on bug fixes and minor performance improvements. You can access the new version here: installers and source code. CUDA Version Updates We have also improved the compatibility of the ArrayFire library to the latest CUDA toolkits and improved the build process and added additional build configurations so that you can customize the library for your specific application. Better Linux Experience We have updated the Debian and Ubuntu installers to reduce the binary size and reduced the setup process for the users. You can now download the ArrayFire library using the following commands on a Debian/Ubuntu system. apt-key adv –fetch-key https://repo.arrayfire.com/GPG-PUB-KEY-ARRAYFIRE-2020.PUB echo …

Classification of Topological Discrepancies in 3D Printing with ArrayFire

John Melonakos Case Studies Leave a Comment

Researchers from the Palo Alto Research Center in California credit ArrayFire in a paper published in the Journal of Computer-Aided Design. The paper is titled “A Classification of Topological Discrepancies in Additive Manufacturing” and showcases a novel approach for classification of local shape deviations in topological terms than can be used to improve 3D printing processes. The OpenCL version of ArrayFire on an NVIDIA GTX 1080 GPU was used for FFT-based convolutions and superlevel set operations. A design’s manufacturability via an additive manufacturing (AM) process is largely determined by the AM machine’s ability to print the shape within ‘acceptable limits’. The notion of geometric dimensioning and tolerancing has been used successfully to define and check these limits for conventionally manufactured …