1 citations · 1 across the 7 of their papers we have counts for
7 papers
SOLAR: AI-Powered Speed-of-Light Performance Analysis
Qijing Huang, Sana Damani, Zhifan Ye +9
How fast could a deep-learning model run on target hardware, and how far is today's implementation from that limit? These questions are central to software, hardware, and algorithm…
AVO: Agentic Variation Operators for Autonomous Evolutionary Search
Terry Chen, Zhifan Ye, Bing Xu +20
Agentic Variation Operators (AVO) are a new family of evolutionary variation operators that replace the fixed mutation, crossover, and hand-designed heuristics of classical evoluti…
SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits
Edward Lin, Sahil Modi, Siva Kumar Sastry Hari +30
As agentic AI systems become increasingly capable of generating and optimizing GPU kernels, progress is constrained by benchmarks that reward speedup over software baselines rather…
Le-DETR: Revisiting Real-Time Detection Transformer with Efficient Encoder Design
Jiannan Huang, Aditya Kane, Fengzhe Zhou +2
Real-time object detection is crucial for real-world applications as it requires high accuracy with low latency. While Detection Transformers (DETR) have demonstrated significant p…
Person Recognition at Altitude and Range: Fusion of Face, Body Shape and Gait
Feng Liu, Nicholas Chimitt, Lanqing Guo +16
We address the problem of whole-body person recognition in unconstrained environments. This problem arises in surveillance scenarios such as those in the IARPA Biometric Recognitio…
Generalized Neighborhood Attention: Multi-dimensional Sparse Attention at the Speed of Light
Ali Hassani, Fengzhe Zhou, Aditya Kane +13
Many sparse attention mechanisms such as Neighborhood Attention have typically failed to consistently deliver speedup over the self attention baseline. This is largely due to the l…
Task Arithmetic with LoRA for Continual Learning
Rajas Chitale, Ankit Vaidya, Aditya Kane +1
Continual learning refers to the problem where the training data is available in sequential chunks, termed "tasks". The majority of progress in continual learning has been stunted…