3 papers
cs.LG2025
Enabling Unstructured Sparse Acceleration on Structured Sparse Accelerators
Geonhwa Jeong, Po-An Tsai, Abhimanyu R. Bambhaniya +2
Exploiting sparsity in deep neural networks (DNNs) has been a promising area for meeting the growing computation requirements. To minimize the overhead of sparse acceleration, hard…
cs.DC2025
GPUArmor: A Hardware-Software Co-design for Efficient and Scalable Memory Safety on GPUs
Mohamed Tarek Ibn Ziad, Sana Damani, Mark Stephenson +2
Memory safety errors continue to pose a significant threat to current computing systems, and graphics processing units (GPUs) are no exception. A prominent class of memory safety a…
cs.AR2025
Kitsune: Enabling Dataflow Execution on GPUs
Michael Davies, Neal Crago, Karthikeyan Sankaralingam +1
State of art DL models are growing in size and complexity, with many modern models also increasing in heterogeneity of behavior. GPUs are still the dominant platform for DL applica…