3 citations · 3 across the 6 of their papers we have counts for
6 papers
Verified Pythagorean Composition for Adaptive Cryptographic Games: Noise Flooding in Homomorphic Encryption
Yi Lee, Alexandru Cojocaru, Junyi Liu +1
Noise flooding is a standard defense against decryption attacks on approximate homomorphic encryption, but its security proof is unusually sensitive to composition. Replacing each…
OasisKV: Scaling In-Decode KV Cache Beyond HBM with Lookahead Sparse Prefetching
Can Xiao, Sukmin Cho, Junbong We +7
Large language model (LLM) inference serving is increasingly constrained by memory rather than compute. As long-context and long-form reasoning workloads become more prevalent, the…
MemExplorer: Navigating the Heterogeneous Memory Design Space for Agentic Inference NPUs
Haoran Wu, Zeyu Cao, Yao Lai +16
Emerging agentic large language model (LLM) workloads are driving rapidly growing demand for memory capacity and bandwidth. Different phases of inference, such as prefill and decod…
A Scalable Open-Source QEC System with Sub-Microsecond Decoding-Feedback Latency
Junyi Liu, Yi Lee, Yilun Xu +2
Quantum error correction (QEC) is essential for realizing large-scale, fault-tolerant quantum computation, yet its practical implementation remains a major engineering challenge. I…
Managed-Retention Memory: A New Class of Memory for the AI Era
Sergey Legtchenko, Ioan Stefanovici, Richard Black +6
AI clusters today are one of the major uses of High Bandwidth Memory (HBM). However, HBM is suboptimal for AI workloads for several reasons. Analysis shows HBM is overprovisioned o…
Good things come in small packages: Should we build AI clusters with Lite-GPUs?
Burcu Canakci, Junyi Liu, Xingbo Wu +5
To match the blooming demand of generative AI workloads, GPU designers have so far been trying to pack more and more compute and memory into single complex and expensive packages.…