11 citations · 14 across the 5 of their papers we have counts for
6 papers
MANTA: Machine Learning Augmented Tiering Advisor
Johannes Freischuetz, Kiet Pham, Sujay Yadalam +3
Memory tiering has been used to expand memory capacity, particularly in datacenters, by combining fast DRAM with slower tiers, including CXL-attached memory. Its effectiveness depe…
Minos: Systematically Classifying Performance and Power Characteristics of GPU Workloads on HPC Clusters
Rutwik Jain, Yiwei Jiang, Matthew D. Sinclair +1
As large-scale HPC compute clusters increasingly adopt accelerators such as GPUs to meet the voracious demands of modern workloads, these clusters are increasingly becoming power c…
Wattchmen: Watching the Wattchers -- High Fidelity, Flexible GPU Energy Modeling
Brandon Tran, Matthias Maiterth, Woong Shin +2
Modern GPU-rich HPC systems are increasingly becoming energy-constrained. Thus, understanding an application's energy consumption becomes essential. Unfortunately, current GPU ener…
ARMS: Adaptive and Robust Memory Tiering System
Sujay Yadalam, Konstantinos Kanellis, Michael Swift +1
Memory tiering systems seek cost-effective memory scaling by adding multiple tiers of memory. For maximum performance, frequently accessed (hot) data must be placed close to the ho…
From Good to Great: Improving Memory Tiering Performance Through Parameter Tuning
Konstantinos Kanellis, Sujay Yadalam, Fanchao Chen +2
Memory tiering systems achieve memory scaling by adding multiple tiers of memory wherein different tiers have different access latencies and bandwidth. For maximum performance, fre…
TUNA: Tuning Unstable and Noisy Cloud Applications
Johannes Freischuetz, Konstantinos Kanellis, Brian Kroth +1
Autotuning plays a pivotal role in optimizing the performance of systems, particularly in large-scale cloud deployments. One of the main challenges in performing autotuning in the…