Cloud computing landscape and research challenges regarding trust and reputation
Cloud Computing is an emerging computing paradigm. It shares massively scalable, elastic
resources (eg, data, calculations, and services) transparently among the users over a …
resources (eg, data, calculations, and services) transparently among the users over a …
MCM-GPU: Multi-chip-module GPUs for continued performance scalability
Historically, improvements in GPU-based high performance computing have been tightly
coupled to transistor scaling. As Moore's law slows down, and the number of transistors per …
coupled to transistor scaling. As Moore's law slows down, and the number of transistors per …
GPGPU performance and power estimation using machine learning
G Wu, JL Greathouse, A Lyashevsky… - 2015 IEEE 21st …, 2015 - ieeexplore.ieee.org
Graphics Processing Units (GPUs) have numerous configuration and design options,
including core frequency, number of parallel compute units (CUs), and available memory …
including core frequency, number of parallel compute units (CUs), and available memory …
Simultaneous multikernel GPU: Multi-tasking throughput processors via fine-grained sharing
Studies show that non-graphics programs can be less optimized for the GPU hardware,
leading to significant resource under-utilization. Sharing the GPU among multiple programs …
leading to significant resource under-utilization. Sharing the GPU among multiple programs …
Chimera: Collaborative preemption for multitasking on a shared GPU
The demand for multitasking on graphics processing units (GPUs) is constantly increasing
as they have become one of the default components on modern computer systems along …
as they have become one of the default components on modern computer systems along …
Heimdall: mobile GPU coordination platform for augmented reality applications
We present Heimdall, a mobile GPU coordination platform for emerging Augmented Reality
(AR) applications. Future AR apps impose an explored challenging workload: i) concurrent …
(AR) applications. Future AR apps impose an explored challenging workload: i) concurrent …
Gme: Gpu-based microarchitectural extensions to accelerate homomorphic encryption
Fully Homomorphic Encryption (FHE) enables the processing of encrypted data without
decrypting it. FHE has garnered significant attention over the past decade as it supports …
decrypting it. FHE has garnered significant attention over the past decade as it supports …
Seastar: vertex-centric programming for graph neural networks
Graph neural networks (GNNs) have achieved breakthrough performance in graph analytics
such as node classification, link prediction and graph clustering. Many GNN training …
such as node classification, link prediction and graph clustering. Many GNN training …
Warped-slicer: Efficient intra-SM slicing through dynamic resource partitioning for GPU multiprogramming
As technology scales, GPUs are forecasted to incorporate an ever-increasing amount of
computing resources to support thread-level parallelism. But even with the best effort …
computing resources to support thread-level parallelism. But even with the best effort …
A fast nonnegative autoencoder-based approach to latent feature analysis on high-dimensional and incomplete data
F Bi, T He, X Luo - IEEE Transactions on Services Computing, 2023 - ieeexplore.ieee.org
High-Dimensional and Incomplete (HDI) data are frequently encountered in various Big
Data-related applications. Despite its incompleteness, an HDI data repository contains rich …
Data-related applications. Despite its incompleteness, an HDI data repository contains rich …