From low-power IoT devices to high-performance computing nodes, energy is often a key consideration. We face multiple significant energy-related challenges: availability, cost, and sustainability, to name only the most frequent. Understanding how the energy is spent is crucial for addressing bottlenecks in both software and hardware aspects. This presentation is twofold. First, we present a low-power audio recording device, a first high-level energy breakdown shows that storage is responsible for half of the total energy usage. Under these conditions, we implement and compare multiple data reduction strategies. Secondly, we take a look into high-performance systems. We propose a methodology to evaluate the energy consumption of GPUs at the instruction level. We base our methodology on measurements provided by a built-in sensor and performance counters reported by profiling tools. Our results show that data movement across the cache hierarchy dominates the energy usage.
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More information :https://www.spintec.fr/seminar-energy-and-computing-identifying-and-addressing-bottlenecks/​

Videoconference ​: https://univ-grenoble-alpes-fr.zoom.us/j/98769867024?pwd=dXNnT3RMeThjYStybGVQSUN0TVdJdz09​​