Posts
Dec, 12
Parallelization of an Ultrasound Reconstruction Algorithm for non Destructive Testing on Multicore CPU and GPU
The CIVA software platform developed by CEA-LIST offers various simulation and data processing modules dedicated to non-destructive testing (NDT). In particular, ultrasonic imaging and reconstruction tools are proposed, in the purpose of localizing echoes and identifying and sizing the detected defects. Because of the complexity of data processed, computation time is now a limitation for […]
Dec, 12
A Rigid Body Physics Engine for Interactive Applications
We have conceived and implemented a software library to be employed in speeding up the development of animations or applications that make use of interactive physics simulation. This paper focuses on the discussion of some of the algorithms and techniques that were used on its basic implementation, and also on expansions and optimizations that were […]
Dec, 12
Parallel Evaluation of a Spatial Traversability Cost Function on GPU for Efficient Path Planning
A parallel version of the traditional grid based cost-to-go function generation algorithm used in robot path planning is introduced. The process takes advantage of the spatial layout of an occupancy grid by concurrently calculating the next wave front of grid cells usually evaluated sequentially in traditional dynamic programming algorithms. The algorithm offers an order of […]
Dec, 12
Accelerating non-linear image registration with GPUs
The alignment or registration of two images or volumetric datasets is frequently a requirement in modern image-processing applications, particularly within the context of medical imaging. Modern graphics-processing units (GPUs) are designed to perform simple 3D graphics-pipeline tasks on a massively parallel scale; this processing power can be harnessed for general computation via libraries such as […]
Dec, 12
GPU Programming in a High Level Language: Compiling X10 to CUDA
GPU architectures have emerged as a viable way of considerably improving performance for appropriate applications. Program fragments (kernels) appropriate for GPU execution can be implemented in CUDA or OpenCL and glued into an application via an API. While there is plenty of evidence of performance improvements using this approach, there are many issues with productivity. […]
Dec, 12
A fast and intuitive visual programming language (VPL) for constructing Computer Vision and Image processing systems on GPUs
In this work we present a novel GPU based Visual Programming Language for Computer Vision and Image Processing systems. Many vision algorithms have been shown to perform better on GPUs. However, one of the current drawbacks is the need for considerable GPU programming expertise. We propose an abstraction over GPU implementation details by providing an […]
Dec, 12
Theano: A CPU and GPU Math Compiler in Python
Theano is a compiler for mathematical expressions in Python that combines the convenience of NumPy’s syntax with the speed of optimized native machine language. The user composes mathematical expressions in a high-level description that mimics NumPy’s syntax and semantics, while being statically typed and functional (as opposed to imperative). These expressions allow Theano to provide […]
Dec, 12
A Common GPU n-Dimensional Array for Python and C
Currently there are multiple incompatible array/matrix/n-dimensional base object implementations for GPUs. This hinders the sharing of GPU code and causes duplicate development work. This paper proposes and presents a first version of a common GPU n-dimensional array(tensor) named GpuNdArray that works with both CUDA and OpenCL. It will be usable from python, C and possibly […]
Dec, 12
Bringing Parallel Performance to Python with Domain-Specific Selective Embedded Just-in-Time Specialization
Today’s productivity programmers, such as scientists who need to write code to do science, are typically forced to choose between productive and maintainable code with modest performance (e.g. Python plus native libraries such as SciPy [SciPy]) or complex, brittle, hardware-specific code that entangles application logic with performance concerns but runs two to three orders of […]
Dec, 11
Self-Supervised Clustering for Codebook Construction: An Application to Object Localization
Approaches to object localization based on codebooks do not exploit the dependencies between appearance and geometric information present in training data. This work addresses the problem of computing a codebook tailored to the task of localization by applying regularization based on geometric information. We present a novel method, the Regularized Combined Partitional-Agglomerative clustering, which extends […]
Dec, 11
Aquila: An Open-Source GPU-Accelerated Toolkit for Cognitive Robotics Research
This paper presents a novel open-source software Aquila developed as a part of the iTalk and RobotDoC projects. This software provides many different tools and biologically inspired systems that are useful for cognitive robotics research. Aquila addresses the need for high-performance robot control by adopting the latest parallel processing paradigm based on the NVidia CUDA […]
Dec, 11
Gyrokinetic Toroidal Simulations on Leading Multi-and Manycore HPC Systems
The gyrokinetic Particle-in-Cell (PIC) method is a critical computational tool enabling petascale fusion simulation research. In this work, we present novel multi- and manycore-centric optimizations to enhance performance of GTC, a PIC-based production code for studying plasma microturbulence in tokamak devices. Our optimizations encompass all six GTC sub-routines and include multi-level particle and grid decompositions […]
