5 papers
D-com: Accelerating Iterative Processing to Enable Low-rank Decomposition of Activations
Faraz Tahmasebi, Michael Pelluer, Hyoukjun Kwon
The computation and memory costs of large language models kept increasing over last decade, which reached over the scale of 1T parameters. To address the challenges from the large…
Exploring the Dynamic Scheduling Space of Real-Time Generative AI Applications on Emerging Heterogeneous Systems
Rachid Karami, Rajeev Patwari, Hyoukjun Kwon +1
The integration of generative AI models, particularly large language models (LLMs), into real-time multi-model AI applications such as video conferencing and gaming is giving rise…
Performance Implications of Multi-Chiplet Neural Processing Units on Autonomous Driving Perception
Mohanad Odema, Luke Chen, Hyoukjun Kwon +1
We study the application of emerging chiplet-based Neural Processing Units to accelerate vehicular AI perception workloads in constrained automotive settings. The motivation stems…
FlexiBit: Fully Flexible Precision Bit-parallel Accelerator Architecture for Arbitrary Mixed Precision AI
Faraz Tahmasebi, Yian Wang, Benji Y. H. Huang +1
Recent research has shown that large language models (LLMs) can utilize low-precision floating point (FP) quantization to deliver high efficiency while maintaining original model a…
Efficient Depth Estimation for Unstable Stereo Camera Systems on AR Glasses
Yongfan Liu, Hyoukjun Kwon
Stereo depth estimation is a fundamental component in augmented reality (AR), which requires low latency for real-time processing. However, preprocessing such as rectification and…