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Posts

Dec, 28

Design and Implementation of the Futhark Programming Language

In this thesis we describe the design and implementation of Futhark, a small data-parallel purely functional array language that offers a machine-neutral programming model, and an optimising compiler that generates efficient OpenCL code for GPUs. The overall philosophy is based on seeking a middle ground between functional and imperative approaches. The specific contributions are as […]
Dec, 28

A Generic Inverted Index Framework for Similarity Search on the GPU

We propose a novel generic inverted index framework on the GPU (called GENIE), aiming to reduce the programming complexity of the GPU for parallel similarity search of different data types. Not every data type and similarity measure are supported by GENIE, but many popular ones are. We present the system design of GENIE, and demonstrate […]
Dec, 28

A Survey of FPGA Based Neural Network Accelerator

Recent researches on neural network have shown great advantage in computer vision over traditional algorithms based on handcrafted features and models. Neural network is now widely adopted in regions like image, speech and video recognition. But the great computation and storage complexity of neural network based algorithms poses great difficulty on its application. CPU platforms […]
Dec, 28

Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

Integrated CPU-GPU architecture provides excellent acceleration capabilities for data parallel applications on embedded platforms while meeting the size, weight and power (SWaP) requirements. However, sharing of main memory between CPU applications and GPU kernels can severely affect the execution of GPU kernels and diminish the performance gain provided by GPU. For example, in the NVIDIA […]
Dec, 24

Pass a Pointer: Exploring Shared Virtual Memory Abstractions in OpenCL Tools for FPGAs

Heterogeneous CPU-FPGA systems are gaining momentum in the embedded systems sector and in the data center market. While the programming abstractions for implementing the data transfer between CPU and FPGA (and vice versa) that are available in today’s commercial programming tools are well-suited for certain types of applications, the CPU-FPGA communication for applications that share […]
Dec, 24

Extending OmpSs for OpenCL kernel co-execution in heterogeneous systems

Heterogeneous systems have a very high potential performance but present difficulties in their programming. OmpSs is a well known framework for task based parallel applications, which is an interesting tool to simplify the programming of these systems. However, it does not support the co-execution of a single OpenCL kernel instance on several compute devices. To […]
Dec, 24

An MPI-Based Python Framework for Distributed Training with Keras

We present a lightweight Python framework for distributed training of neural networks on multiple GPUs or CPUs. The framework is built on the popular Keras machine learning library. The Message Passing Interface (MPI) protocol is used to coordinate the training process, and the system is well suited for job submission at supercomputing sites. We detail […]
Dec, 24

An In-depth Performance Characterization of CPU- and GPU-based DNN Training on Modern Architectures

Traditionally, Deep Learning (DL) frameworks like Caffe, TensorFlow, and Cognitive Toolkit exploited GPUs to accelerate the training process. This has been primarily achieved by aggressive improvements in parallel hardware as well as through sophisticated software frameworks like cuDNN and cuBLAS. However, recent enhancements to CPU-based hardware and software has the potential to significantly enhance the […]
Dec, 24

GAMER-2: a GPU-accelerated adaptive mesh refinement code — accuracy, performance, and scalability

We present GAMER-2, a GPU-accelerated adaptive mesh refinement (AMR) code for astrophysics. It provides a rich set of features, including adaptive time-stepping, several hydrodynamic schemes, magnetohydrodynamics, self-gravity, particles, star formation, chemistry and radiative processes with GRACKLE, data analysis with yt, and memory pool for efficient object allocation. GAMER-2 is fully bitwise reproducible. For the performance […]
Dec, 19

Molecular dynamics recipes for genome research

Molecular dynamics (MD) simulation allows one to predict the time evolution of a system of interacting particles. It is widely used in physics, chemistry and biology to address specific questions about the structural properties and dynamical mechanisms of model systems. MD earned a great success in genome research, as it proved to be beneficial in […]
Dec, 19

Accelerated Sparse Matrix Operations in Nonlinear Least Squares Solvers

This thesis focuses on data structures for sparse block matrices and the associated algorithms for performing linear algebra operations that I have developed. Sparse block matrices occur naturally in many key problems, such as Nonlinear LEast Squares (NLS) on graphical models. NLS are used by e.g. Simultaneous Localization and Mapping (SLAM) in robotics, Bundle Adjustment […]
Dec, 19

OpenCL-accelerated Point Feature Histogram and Its Application in Railway Track Point Cloud Data Processing

To meet the requirements of railway track point cloud processing, an OpenCL-accelerated Point Feature Histogram method is proposed using heterogeneous computing to improve the low computation efficiency. According to the characteristics of parallel computing of OpenCL, the data structure for point cloud storage is reconfigured. With the kernel performance analysis by CodeXL, the data reading […]
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