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Posts

Feb, 10

Programming GPUs with C++14 and Just-In-Time Compilation

Systems that comprise accelerators (e.g., GPUs) promise high performance, but their programming is still a challenge, mainly because of two reasons: 1) two distinct programming models have to be used within an application: one for the host CPU (e.g., C++), and one for the accelerator (e.g., OpenCL or CUDA); 2) using Just-In-Time (JIT) compilation and […]
Feb, 10

BinaryNet: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

We introduce BinaryNet, a method which trains DNNs with binary weights and activations when computing parameters’ gradient. We show that it is possible to train a Multi Layer Perceptron (MLP) on MNIST and ConvNets on CIFAR-10 and SVHN with BinaryNet and achieve nearly state-of-the-art results. At run-time, BinaryNet drastically reduces memory usage and replaces most […]
Feb, 9

Guided Profiling for Auto-Tuning Array Layouts on GPUs

Auto-tuning for Graphics Processing Units (GPUs) has become very popular in recent years. It removes the necessity to hand-tune GPU code especially when a new hardware architecture is released. Our auto-tuner optimizes memory access patterns. This is a key aspect to exploit the full performance of modern GPUs. As the memory hierarchy has historically changed […]
Feb, 8

Portable Programming Models for Heterogeneous Platforms

With the end of Dennard scaling and emergence of dark silicon, the bets are high on heterogeneous architectures to achieve both application performance and energy efficiency. However, diversity in heterogeneous architectures poses severe programming challenges in terms of data layout, memory coherence, task partitioning, data distribution, and sharing of virtual addresses. Existing high-level programming languages […]
Feb, 8

High performance high-order numerical methods: applications in ocean modeling

This thesis presents high-order numerical methods for time-dependent simulations of oceanic wave propagation on modern many-core hardware architecture. Simulation of the waves such as tsunami, is challenging because of the varying fluid depths, propagation in many regions, requirement of high resolution near the shore, complex nonlinear wave phenomenon, and necessity of faster than real-time predictions. […]
Feb, 8

Utilizing GPUs to Accelerate Turbomachinery CFD Codes

GPU computing has established itself as a way to accelerate parallel codes in the high performance computing world. This work focuses on speeding up APNASA, a legacy CFD code used at NASA Glenn Research Center, while also drawing conclusions about the nature of GPU computing and the requirements to make GPGPU worthwhile on legacy codes. […]
Feb, 8

Workload distribution and balancing in FPGAs and CPUs with OpenCL and TBB

In this paper we evaluate the performance and energy effectiveness of FPGA and CPU devices for a kind of parallel computing applications in which the workload can be distributed in a way that enables simultaneous computing in addition to simple off loading. The FPGA device is programmed via OpenCL using the recent availability of commercial […]
Feb, 8

Integrating GPGPU computations with CPU coroutines in C++

We present results on integration of two major GPGPU APIs with reactor-based event processing model in C++ that utilizes coroutines. With current lack of universally usable GPGPU programming interface that gives optimal performance and debates about the style of implementing asynchronous computing in C++, we present a working implementation that allows a uniform and seamless […]
Feb, 8

Collaborative design and optimization using Collective Knowledge

Designing faster, more energy efficient and reliable computer systems requires effective collaboration between hardware designers, system programmers and performance analysts, as well as feedback from system users. We present Collective Knowledge (CK), an open framework for reproducible and collaborative design and optimization. CK enables systematic and reproducible experimentation, combined with leading edge predictive analytics to […]
Feb, 6

GPU Hackathons, 2016

Background General-purpose Graphics Processing Units (GPGPUs) potentially offer exceptionally high memory bandwidth and performance for a wide range of applications. The challenge in utilizing such accelerators has been the difficulty in programming them. The OpenACC Directives for Accelerators offers straightforward pragma extensions to C++ and Fortran to address this programming hurdle, but other GPU programming […]
Feb, 6

Impact of data layouts on the efficiency of GPU-accelerated IDW interpolation

This paper focuses on evaluating the impact of different data layouts on the computational efficiency of GPU-accelerated Inverse Distance Weighting (IDW) interpolation algorithm. First we redesign and improve our previous GPU implementation that was performed by exploiting the feature of CUDA dynamic parallelism (CDP). Then we implement three versions of GPU implementations, i.e., the naive […]
Feb, 6

PRISM-PSY: Precise GPU-Accelerated Parameter Synthesis for Stochastic Systems

In this paper we present PRISM-PSY, a novel tool that performs precise GPU-accelerated parameter synthesis for continuous-time Markov chains and time-bounded temporal logic specifications. We redesign, in terms of matrix-vector operations, the recently formulated algorithms for precise parameter synthesis in order to enable effective dataparallel processing, which results in significant acceleration on many-core architectures. High […]
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