high performance computing on graphics processing units: hgpu.org

Fast Fourier Transform (FFT) is an essential tool in scientific and engineering computation. The increasing demand for mixed-precision FFT has made it possible to utilize half-precision floating-point (FP16) arithmetic for faster speed and energy saving. Specializing in lower precision, NVIDIA Tensor Cores can deliver extremely high computation performance. However, the fixed computation pattern makes it […]

GPUs are now used for a wide range of problems within HPC. However, making efficient use of the computational power available with multiple GPUs is challenging. The main challenges in achieving good performance are memory layout, affecting memory bandwidth, effective use of the memory spaces with a GPU, inter-GPU communication, and synchronization. We address these […]

It has been increasingly challenging for the compilers to cope with the evolving computer architectures. The manually written compiler heuristics are not sufficiently wise to capture the impact of data and hardware related dependencies on performance. However, machine learning offers an opportunity to learn the common patterns in the existing dataset and predict the future […]

GPUs are now used for a wide range of problems within HPC. However, making efficient use of the computational power available with multiple GPUs is challenging. The main challenges in achieving good performance are memory layout, affecting memory bandwidth, effective use of the memory spaces with a GPU, inter-GPU communication, and synchronization. We address these […]

We introduce CryptGPU, a system for privacy-preserving machine learning that implements all operations on the GPU (graphics processing unit). Just as GPUs played a pivotal role in the success of modern deep learning, they are also essential for realizing scalable privacy-preserving deep learning. In this work, we start by introducing a new interface to losslessly […]

Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) bring unprecedented performance requirements for automotive systems. Graphic Processing Unit (GPU) based platforms have been deployed with the aim of meeting these requirements, being NVIDIA Jetson TX2 and its high-performance successor, NVIDIA AGX Xavier, relevant representatives. However, to what extent high-performance GPU configurations are appropriate for […]

SLATE implements GPU-accelerated linear algebra, relying primarily on vendor-provided GPU BLAS for performance, in particular batched BLAS routines. Initially, SLATE was written using NVIDIA’s CUDA and cuBLAS for GPU acceleration. At the time that the SLATE project was started, it was unclear what GPU technologies would exist for other platforms [1]. Since then, AMD has […]

Large-scale sorting is always an important yet demanding task for data center applications. In addition to powerful processing capability, high-performance sorting system requires efficient utilization of the available bandwidth of various levels in the memory hierarchy. Nowadays, with the explosive data size, the frequent data transfers between the host and the storage device are becoming […]

As the computing hardware landscape gets more diverse, and the complexity of hardware grows, the need for a general purpose parallel programming model capable of developing (performance) portable codes have become highly attractive. Intel’s OneAPI suite, which is based on the SYCL standard aims to fill this gap using a modern C++ API. In this […]

Large language models have led to state-of-the-art accuracies across a range of tasks. However, training these large models efficiently is challenging for two reasons: a) GPU memory capacity is limited, making it impossible to fit large models on a single GPU or even on a multi-GPU server; and b) the number of compute operations required […]

Recently, Deep Neural Networks (DNNs) have recorded great success in handling medical and other complex classification tasks. However, as the sizes of a DNN model and the available dataset increase, the training process becomes more complex and computationally intensive, which usually takes a longer time to complete. In this work, we have proposed a generic […]

Modern commodity devices are nowadays equipped with a plethora of heterogeneous devices serving different purposes. Being able to exploit such heterogeneous hardware accelerators to their full potential is of paramount importance in the pursuit of higher performance and energy efficiency. Towards these objectives, the reduction of idle time of each device as well as the […]