High-performance computing relies on performance-oriented infrastructures with access to
powerful computing resources to complete tasks that contribute to solve complex problems …

The rapid growth in demand for HPC systems has led to a rise in carbon footprint, which
requires urgent intervention. In this work, we present a comprehensive analysis of the …

GPUs are widely used to accelerate the training of machine learning workloads. As modern
machine learning models become increasingly larger, they require a longer time to train …

The challenges to push computing to exaflop levels are difficult given desired targets for
memory capacity, memory bandwidth, power efficiency, reliability, and cost. This paper …

Dynamic Voltage and Frequency Scaling (DVFS) on Graphics Processing Units (GPUs)
components is one of the most promising power management strategies, due to its potential …

Characterizing compute kernel execution behavior on GPUs for efficient task scheduling is a
non-trivial task. We address this with a simple model enabling portable and fast predictions …

As Moore's law slows down, GPUs must pivot towards multi-module designs to continue
scaling performance at historical rates. Prior work on multi-module GPUs has focused on …

The Register File (RF) in GPUs is a critical structure that maintains the state for thousands of
threads that support the GPU processing model. The RF organization substantially affects …

Dynamic voltage and frequency scaling (DVFS) is a popular technique to improve the
energy-efficiency of high-performance computing systems. It allows placing the devices into …

The Register File (RF) is a critical structure in Graphics Processing Units (GPUs) responsible
for a large portion of the area and power. To simplify the architecture of the RF, it is …