44 citations · 89 across the 11 of their papers we have counts for
12 papers
SENSEi: Input-Sensitive Compilation for Accelerating GNNs
Damitha Lenadora, Vimarsh Sathia, Gerasimos Gerogiannis +3
Over the years, many frameworks and optimization techniques have been proposed to accelerate graph neural networks (GNNs). Compared to the optimizations explored in these systems,…
Defensive ML: Defending Architectural Side-channels with Adversarial Obfuscation
Hyoungwook Nam, Raghavendra Pradyumna Pothukuchi, Bo Li +2
Side-channel attacks that use machine learning (ML) for signal analysis have become prominent threats to computer security, as ML models easily find patterns in signals. To address…
UniHeap: Managing Persistent Objects Across Managed Runtimes for Non-Volatile Memory
Daixuan Li, Benjamin Reidys, Jinghan Sun +3
Byte-addressable, non-volatile memory (NVM) is emerging as a promising technology. To facilitate its wide adoption, employing NVM in managed runtimes like JVM has proven to be an e…
A Method for Hiding the Increased Non-Volatile Cache Read Latency
Apostolos Kokolis, Namrata Mantri, Shrikanth Ganapathy +2
The increased memory demands of workloads is putting high pressure on Last Level Caches (LLCs). Unfortunately, there is limited opportunity to increase the capacity of LLCs due to…
Speculative Interference Attacks: Breaking Invisible Speculation Schemes
Mohammad Behnia, Prateek Sahu, Riccardo Paccagnella +13
Recent security vulnerabilities that target speculative execution (e.g., Spectre) present a significant challenge for processor design. The highly publicized vulnerability uses spe…
SparseTrain:Leveraging Dynamic Sparsity in Training DNNs on General-Purpose SIMD Processors
Zhangxiaowen Gong, Houxiang Ji, Christopher Fletcher +2
Our community has greatly improved the efficiency of deep learning applications, including by exploiting sparsity in inputs. Most of that work, though, is for inference, where weig…