Related papers: PowerSensor3: A Fast and Accurate Open Source Powe…
The rapid growth of data volume brings big challenges to the data center computing, and energy efficiency is one of the most concerned problems. Researchers from various fields are now proposing solutions to green the data center…
Energy-centric design is paramount in the current embedded computing era: use cases require increasingly high performance at an affordable power budget, often under real-time constraints. Hardware heterogeneity and parallelism help address…
Recent years have witnessed a phenomenal growth in the computational capabilities and applications of GPUs. However, this trend has also led to dramatic increase in their power consumption. This paper surveys research works on analyzing and…
In the current high-performance and embedded computing era, full-stack energy-centric design is paramount. Use cases require increasingly high performance at an affordable power budget, often under real-time constraints. Extreme…
Introducing HyperSense, our co-designed hardware and software system efficiently controls Analog-to-Digital Converter (ADC) modules' data generation rate based on object presence predictions in sensor data. Addressing challenges posed by…
Today, deep learning optimization is primarily driven by research focused on achieving high inference accuracy and reducing latency. However, the energy efficiency aspect is often overlooked, possibly due to a lack of sustainability mindset…
High-performance computing (HPC) and supercomputing are critical in Artificial Intelligence (AI) research, development, and deployment. The extensive use of supercomputers for training complex AI models, which can take from days to months,…
As AI workloads drive increases in datacenter power consumption, accurate GPU power estimation is critical for proactive power management. However, existing power models face a scalability bottleneck not in the modeling techniques…
The ongoing integration of fine-grained power management features already established in CPU-driven Systems-on-Chip (SoCs) enables both traditional Field Programmable Gate Arrays (FPGAs) and, more recently, hybrid Programmable SoCs (pSoCs)…
With high-performance computing systems now running at exascale, optimizing power-scaling management and resource utilization has become more critical than ever. This paper explores runtime power-capping optimizations that leverage…
Accurate software energy measurement is critical for optimizing energy, yet existing profilers force a trade-off between measurement accuracy and overhead due to tight coupling with supported specific hardware or languages. We present…
To address the challenge of performance analysis on the US DOE's forthcoming exascale supercomputers, Rice University has been extending its HPCToolkit performance tools to support measurement and analysis of GPU-accelerated applications.…
In the continually evolving realm of software engineering, the need to address software energy consumption has gained increasing prominence. However, the absence of a platform-independent tool that facilitates straightforward energy…
This paper presents a novel approach to event-based power modelling for embedded platforms that do not have a Performance Monitoring Unit (PMU). The method involves complementing the target hardware platform, where the physical power data…
Modern GPU-rich HPC systems are increasingly becoming energy-constrained. Thus, understanding an application's energy consumption becomes essential. Unfortunately, current GPU energy attribution techniques are either inaccurate, inflexible,…
Energy efficiency has emerged as a central challenge for modern high-performance computing (HPC) systems, where escalating computational demands and architectural complexity have led to significant energy footprints. This paper presents the…
Main memory's rising energy consumption has emerged as a critical challenge in modern computing architectures, particularly in large-scale systems, driven by frequent access patterns, growing data volumes, and insufficient power management…
In Cloud Computing platforms the addition of hardware monitoring devices to gather power usage data can be impractical or uneconomical due to the large number of machines to be metered. CloudMonitor, a monitoring tool that can generate…
Phasor measurement units (PMUs) provide a high-resolution view of the power system at the locations where they are placed. As such, it is desirable to place them in bulk in low voltage distribution circuits. However, the power consumption…
As research and deployment of AI grows, the computational burden to support and sustain its progress inevitably does too. To train or fine-tune state-of-the-art models in NLP, computer vision, etc., some form of AI hardware acceleration is…