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Posts

Feb, 16

EASYPAP: a Framework for Learning Parallel Programming

This paper presents EASYPAP, an easy-to-use programming environment designed to help students to learn parallel programming. EASYPAP features a wide range of 2D computation kernels that the students are invited to parallelize using Pthreads, OpenMP, OpenCL or MPI. Execution of kernels can be interactively visualized, and powerful monitoring tools allow students to observe both the […]
Feb, 16

ISM2: Optimizing Irregular-Shaped Matrix-Matrix Multiplication on GPUs

Linear algebra operations have been widely used in big data analytics and scientific computations. Many works have been done on optimizing linear algebra operations on GPUs with regular-shaped input. However, few works are focusing on fully utilizing GPU resources when the input is not regular-shaped. Current optimizations lack of considering fully utilizing the memory bandwidth […]
Feb, 16

LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment

Pairwise sequence alignment is one of the most computationally intensive kernels in genomic data analysis, accounting for more than 90% of the runtime for key bioinformatics applications. This method is particularly expensive for third-generation sequences due to the high computational cost of analyzing sequences of length between 1Kb and 1Mb. Given the quadratic overhead of […]
Feb, 16

Task-based, GPU-accelerated and Robust Library for Solving Dense Nonsymmetric Eigenvalue Problems

In this paper, we present the StarNEig library for solving dense nonsymmetric standard and generalized eigenvalue problems. The library is built on top of the StarPU runtime system and targets both shared and distributed memory machines. Some components of the library have support for GPU acceleration. The library is currently in an early beta state […]
Feb, 9

Working With Incremental Spatial Data During Parallel (GPU) Computation

Central to many complex systems, spatial actors require an awareness of their local environment to enable behaviours such as communication and navigation. Complex system simulations represent this behaviour with Fixed Radius Near Neighbours (FRNN) search. This algorithm allows actors to store data at spatial locations and then query the data structure to find all data […]
Feb, 9

Automated Runtime Analysis and Adaptation for Scalable Heterogeneous Computing

In the last decade, there have been tectonic shifts in computer hardware because of reaching the physical limits of the sequential CPU performance. As a consequence, current high-performance computing (HPC) systems integrate a wide variety of compute resources with different capabilities and execution models, ranging from multi-core CPUs to many-core accelerators. While such heterogeneous systems […]
Feb, 9

TC-CIM: Empowering Tensor Comprehensions for Computing-In-Memory

Memristor-based, non-von-Neumann architectures performing tensor operations directly in memory are a promising approach to address the ever-increasing demand for energy-efficient, high-throughput hardware accelerators for Machine Learning (ML) inference. A major challenge for the programmability and exploitation of such Computing-InMemory (CIM) architectures consists in the efficient mapping of tensor operations from high-level ML frameworks to fixed-function […]
Feb, 9

A Language for Describing Optimization Strategies

Optimizing programs to run efficiently on modern parallel hardware is hard but crucial for many applications. The predominantly used imperative languages – like C or OpenCL – force the programmer to intertwine the code describing functionality and optimizations. This results in a nightmare for portability which is particularly problematic given the accelerating trend towards specialized […]
Feb, 9

MKPipe: A Compiler Framework for Optimizing Multi-Kernel Workloads in OpenCL for FPGA

OpenCL for FPGA enables developers to design FPGAs using a programming model similar for processors. Recent works have shown that code optimization at the OpenCL level is important to achieve high computational efficiency. However, existing works either focus primarily on optimizing single kernels or solely depend on channels to design multi-kernel pipelines. In this paper, […]
Feb, 2

GPU-accelerated dynamic programming for join-order optimization

Relational databases need to select efficient join orders, as inefficient join orders can increase the query execution time by several orders of magnitude. To select efficient join orders, relational databases can apply an exhaustive search using dynamic programming. Unfortunately, the applicability of sequential dynamic programming variants is limited to simple queries due to the exhaustive […]
Feb, 2

Non-Determinism in TensorFlow ResNets

We show that the stochasticity in training ResNets for image classification on GPUs in TensorFlow is dominated by the non-determinism from GPUs, rather than by the initialisation of the weights and biases of the network or by the sequence of minibatches given. The standard deviation of test set accuracy is 0.02 with fixed seeds, compared […]
Feb, 2

Optimization of a discontinuous Galerkin solver with OpenCL and StarPU

Since the recent advance in microprocessor design, the optimization of computing software becomes more and more technical. One of the difficulties is to transform sequential algorithms into parallel ones. A possible solution is the task-based design. In this approach, it is possible to describe the parallelization possibilities of the algorithm automatically. The task-based design is […]

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