25 citations · 50 across the 6 of their papers we have counts for
3 papers · 1 filter
A Tale of Two Scales: Reconciling Horizontal and Vertical Scaling for Inference Serving Systems
Kamran Razavi, Mehran Salmani, Max Mühlhäuser +2
Inference serving is of great importance in deploying machine learning models in real-world applications, ensuring efficient processing and quick responses to inference requests. H…
Sponge: Inference Serving with Dynamic SLOs Using In-Place Vertical Scaling
Kamran Razavi, Saeid Ghafouri, Max Mühlhäuser +2
Mobile and IoT applications increasingly adopt deep learning inference to provide intelligence. Inference requests are typically sent to a cloud infrastructure over a wireless netw…
IPA: Inference Pipeline Adaptation to Achieve High Accuracy and Cost-Efficiency
Saeid Ghafouri, Kamran Razavi, Mehran Salmani +5
Efficiently optimizing multi-model inference pipelines for fast, accurate, and cost-effective inference is a crucial challenge in machine learning production systems, given their t…