Posts
Jul, 16
Finite Element Integration with Quadrature on the GPU
We present a novel, quadrature-based finite element integration method for low-order elements on GPUs, using a pattern we call thread transposition to avoid reductions while vectorizing aggressively. On the NVIDIA GTX580, which has a nominal single precision peak flop rate of 1.5 TF/s and a memory bandwidth of 192 GB/s, we achieve close to 300 […]
Jul, 16
GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing
Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking […]
Jul, 16
Accelerating Eulerian Fluid Simulation With Convolutional Networks
Real-time simulation of fluid and smoke is a long standing problem in computer graphics, where state-of-the-art approaches require large compute resources, making real-time applications often impractical. In this work, we propose a data-driven approach that leverages the approximation power of deep-learning methods with the precision of standard fluid solvers to obtain both fast and highly […]
Jul, 13
GPU Accelerated Discrete Element Method (DEM) Molecular Dynamics for Conservative, Faceted Particle Simulations
Faceted shapes, such as polyhedra, are commonly found in systems of nanoscale, colloidal, and granular particles. Many interesting physical phenomena, like crystal nucleation and growth, vacancy motion, and glassy dynamics are challenging to model in these systems because they require detailed dynamical information at the individual particle level. Within the granular materials community the Discrete […]
Jul, 13
Survey of Domain-Specific Languages for FPGA Computing
High-performance FPGA programming has typically been the exclusive domain of a small band of specialized hardware developers. They are capable of reasoning about implementation concerns at the register-transfer level (RTL) which is analogous to assembly-level programming in software. Sometimes these developers are required to push further down to manage even lower levels of abstraction closer […]
Jul, 13
OpenFace: A general-purpose face recognition library with mobile applications
Cameras are becoming ubiquitous in the Internet of Things (IoT) and can use face recognition technology to improve context. There is a large accuracy gap between today’s publicly available face recognition systems and the state-of-the-art private face recognition systems. This paper presents our OpenFace face recognition library that bridges this accuracy gap. We show that […]
Jul, 13
LU, QR, and Cholesky factorizations: Programming Model, Performance Analysis and Optimization Techniques for the Intel Knights Landing Xeon Phi
A wide variety of heterogeneous compute resources, ranging from multicore CPUs to GPUs and coprocessors, are available to modern computers, making it challenging to design unified numerical libraries that efficiently and productively use all these varied resources. For example, in order to efficiently use Intel’s Knights Langing (KNL) processor, the next-generation of Xeon Phi architectures, […]
Jul, 13
The Vectorization of the Tersoff Multi-Body Potential: An Exercise in Performance Portability
Molecular dynamics simulations, an indispensable research tool in computational chemistry and materials science, consume a significant portion of the supercomputing cycles around the world. We focus on multi-body potentials and aim at achieving performance portability. Compared with well-studied pair potentials, multibody potentials deliver increased simulation accuracy but are too complex for effective compiler optimization. Because […]
Jul, 11
Using Deep Convolutional Neural Networks in Monte Carlo Tree Search
Deep Convolutional Neural Networks have revolutionized Computer Go. Large networks have emerged as state-of-the-art models for move prediction and are used not only as stand-alone players but also inside Monte Carlo Tree Search to select and bias moves. Using neural networks inside the tree search is a challenge due to their slow execution time even […]
Jul, 11
Comparing Parallel Hardware Architectures for Visually Guided Robot Navigation
Local visual homing methods are a family of algorithms for visually guided navigation on mobile robots. Within this family, the so-called Min-Warping algorithm yields very precise results but is rather compute-intensive. For this reason, we developed several implementations of this algorithm for different parallel hardware architectures (multi-core CPUs with SIMD extensions, GPUs, FPGA) to arrive […]
Jul, 11
Large Scale GPU Accelerated PPMLR-MHD Simulations for Space Weather Forecast
PPMLR-MHD is a new magnetohydrodynamics (MHD) model used to simulate the interactions of the solar wind with the magnetosphere, which has been proved to be the key element of the space weather cause-and-effect chain process from the Sun to Earth. Compared to existing MHD methods, PPMLR-MHD achieves the advantage of high order spatial accuracy and […]
Jul, 11
Deep Learning for Mortgage Risk
This paper analyzes multi-period mortgage risk at loan and pool levels using an unprecedented dataset of over 120 million prime and subprime mortgages originated across the United States between 1995 and 2014, which includes the individual characteristics of each loan, monthly updates on loan performance over the life of a loan, and a number of […]