Design of a GPU with Heterogeneous Cores for Graphics
Aurora Tom\'as, Juan Luis Arag\'on, Joan Manuel Parcerisa, Antonio Gonz\'alez

TL;DR
This paper introduces KHEPRI, a heterogeneous GPU architecture with specialized cores and a dynamic scheduler that predicts tile behavior, resulting in improved performance and energy efficiency for graphics applications.
Contribution
The paper presents a novel heterogeneous GPU design with a dynamic scheduler that leverages frame coherence for better workload distribution.
Findings
Average performance improvement of 9.2% over traditional GPUs
Throughput increase of 7.3% in frames per second
Total GPU energy reduction of 4.8%
Abstract
Heterogeneous architectures can deliver higher performance and energy efficiency than symmetric counterparts by using multiple architectures tuned to different types of workloads. While previous works focused on CPUs, this work extends the concept of heterogeneity to GPUs by proposing KHEPRI, a heterogeneous GPU architecture for graphics applications. Scenes in graphics applications showcase diversity, as they consist of many objects with varying levels of complexity. As a result, computational intensity and memory bandwidth requirements differ significantly across different regions of each scene. To address this variability, our proposal includes two types of cores: cores optimized for high ILP (compute-specialized) and cores that tolerate a higher number of simultaneously outstanding cache misses (memory-specialized). A key component of the proposed architecture is a novel work…
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Taxonomy
TopicsParallel Computing and Optimization Techniques · Computer Graphics and Visualization Techniques · Embedded Systems Design Techniques
