high performance computing on graphics processing units: hgpu.org

We created an efficient algorithm suitable for graphics processing units (GPUs) to perform Monte Carlo simulations of a subset of reaction-diffusion models. The algorithm uses techniques that are specific to GPU programming, and combines these with the multispin technique known from CPU programming to create one of the fastest algorithms for reaction-diffusion models. As an […]

As GPU hardware becomes increasingly general-purpose, it is quickly outgrowing the traditional, constrained GPU-as-coprocessor programming model. To make GPUs easier to program and improve their integration with operating systems, we propose making the host’s file system directly accessible to GPU code. GPUfs provides a POSIX-like API for GPU programs, exploits GPU parallelism for efficiency, and […]

Over the last decades parallel-distributed computing becomes most popular than traditional centralized computing. In distributed computing performance up-gradation is achieved by distributing workloads across the participating nodes. One of the most important factors for improving the performance of this type of system is to reduce average and standard deviation of job response time. Runtime insertion […]

The paper highlights the question of the optimal GPU computers selection for kernels in OpenCL when they are starting on heterogeneous clusters where different types of GPU are used. The authors propose optimal GPU selection algorithm that helps to get the best efficiency while program execution using GPU.

Graphics Processing Units (GPUs) have evolved to devices with teraflop-level performance potential. Application developers have a tedious task in developing GPU software by correctly identifying parallel computation and optimizing placement of data for the parallel processors in such architectures. Further, code optimized for one architecture may not perform well on different generations of even the […]

GPUs are flexible parallel processors capable of accelerating real applications. To exploit them, programmers rewrite programs in new languages using intimate knowledge of the underlying hardware. This is a step backwards in abstraction and ease of use from sequential programming. When implementing sequential applications, programmers focus on high-level algorithmic concerns, allowing the compiler to target […]

Our problem is to accurately solve linear systems on a general purpose graphics processing unit with double double and quad double arithmetic. The linear systems originate from the application of Newton’s method on polynomial systems. Newton’s method is applied as a corrector in a path following method, so the linear systems are solved in sequence […]

We show that a recently proposed regularization method called random dropouts works well for language models based on neural networks when little training data is available. Random dropout regularization involves adding a certain kind of noise to the likelihood function being optimized and can be interpreted as a variational approximation to a new class of […]

Most recent HPC platforms have heterogeneous nodes composed of a combination of multi-core CPUs and accelerators, like GPUs. Scheduling on such architectures relies on a static partitioning and cost model. In this paper, we present a locality-aware work stealing scheduler for multi-CPU and multi-GPU architectures, which relies on the XKaapi runtime system. We show performance […]

This work concerns the numerical simulation of the Vlasov-Poisson set of equations using semi- Lagrangian methods on Graphical Processing Units (GPU). To accomplish this goal, modifications to traditional methods had to be implemented. First and foremost, a reformulation of semi-Lagrangian methods is performed, which enables us to rewrite the governing equations as a circulant matrix […]

In this paper, we present a GPU-accelerated direct-sum boundary integral method to solve the linear Poisson-Boltzmann (PB) equation. In our method, a well-posed boundary integral formulation is used to ensure the fast convergence of Krylov subspace based linear algebraic solver such as the GMRES. The molecular surfaces are discretized with flat triangles and centroid collocation. […]

With the advent of low-energy buildings, the need for accurate building performance simulations has significantly increased. However, for the time being, the thermo-aeraulic effects are often taken into account through simplified or even empirical models, which fail to provide the expected accuracy. Resorting to computational fluid dynamics seems therefore unavoidable, but the required computational effort […]