Results 81 to 90 of about 15,151 (210)
, 2015 In this report we present a novel approach to model coupling for shared-memory multicore systems hosting OpenCL-compliant accelerators, which we call The Glasgow Model Coupling Framework (GMCF).
Vanderbauwhede, Wim
core
, 2017 ALICE (A Large Heavy Ion Experiment) is one of the four major experiments at the Large Hadron Collider (LHC) at CERN, which is today the most powerful particle accelerator worldwide.
Breitner, Timo +5 more
core +1 more source
Relativistic Hydrodynamics on Graphic Cards
, 2012 We show how to accelerate relativistic hydrodynamics simulations using graphic cards (graphic processing units, GPUs). These improvements are of highest relevance e.g. to the field of high-energetic nucleus-nucleus collisions at RHIC and LHC where (ideal
Bleicher, Marcus +2 more
core +1 more source
Design of Neko—A Scalable High‐Fidelity Simulation Framework With Extensive Accelerator Support
Concurrency and Computation: Practice and Experience, Volume 37, Issue 2, 25 January 2025.ABSTRACT Recent trends and advancements in including more diverse and heterogeneous hardware in High‐Performance Computing (HPC) are challenging scientific software developers in their pursuit of efficient numerical methods with sustained performance across a diverse set of platforms.
Niclas Jansson +4 more
wiley +1 more source
From GPU to CPU (and Beyond): Extending Hardware Support in GPUSPH Through a SYCL‐Inspired Interface
Concurrency and Computation: Practice and Experience, Volume 37, Issue 1, 10 January 2025.ABSTRACT While most software is originally designed for serial or parallel execution on CPU, and porting to GPU comes later in its development, GPUSPH was designed from the ground up to run on GPUs using CUDA. Making it accessible to a wider audience by introducing support for other computational hardware, and in particular CPUs, poses challenges that ...
Giuseppe Bilotta
wiley +1 more source
Loo.py: transformation-based code generation for GPUs and CPUs
, 2014 Today's highly heterogeneous computing landscape places a burden on programmers wanting to achieve high performance on a reasonably broad cross-section of machines.
Asanovic K., Ellson J., Rubinsteyn A.
core +1 more source
Fast Automatic Differentiation for Large Scale Bundle Adjustment
IEEE Access, 2018 A parallelized implementation of automatic differentiation that derives from the problem of bundle adjustment is proposed in this paper. Reverse mode of automatic differentiation is more efficient to compute the derivatives of functions with n real-value
Yan Shen, Yuxing Dai
doaj +1 more source
Sapporo2: A versatile direct $N$-body library
, 2015 Astrophysical direct $N$-body methods have been one of the first production algorithms to be implemented using NVIDIA's CUDA architecture. Now, almost seven years later, the GPU is the most used accelerator device in astronomy for simulating stellar ...
Bédorf, Jeroen +2 more
core +1 more source
Random Finite Set Based Bayesian Filtering with OpenCL in a Heterogeneous Platform
Sensors, 2017 While most filtering approaches based on random finite sets have focused on improving performance, in this paper, we argue that computation times are very important in order to enable real-time applications such as pedestrian detection. Towards this goal,
Biao Hu +7 more
doaj +1 more source