8 citations · 10 across the 5 of their papers we have counts for
6 papers
EWSJF: An Adaptive Scheduler with Hybrid Partitioning for Mixed-Workload LLM Inference
Bronislav Sidik, Chaya Levi, Joseph Kampeas
Serving Large Language Models (LLMs) under mixed workloads--short, latency-sensitive interactive queries alongside long, throughput-oriented batch requests--poses a fundamental sch…
Joint Encoding of KV-Cache Blocks for Scalable LLM Serving
Joseph Kampeas, Emir Haleva
Modern large language models (LLMs) drive interactive AI systems but are bottlenecked by the memory-heavy growth of key-value (KV) caches, which limits real-time throughput under c…
Linear Log-Normal Attention with Unbiased Concentration
Yury Nahshan, Joseph Kampeas, Emir Haleva
Transformer models have achieved remarkable results in a wide range of applications. However, their scalability is hampered by the quadratic time and memory complexity of the self-…
Rotation Invariant Quantization for Model Compression
Joseph Kampeas, Yury Nahshan, Hanoch Kremer +4
Post-training Neural Network (NN) model compression is an attractive approach for deploying large, memory-consuming models on devices with limited memory resources. In this study,…
On Secrecy Rates and Outage in Multi-User Multi-Eavesdroppers MISO Systems
Joseph Kampeas, Asaf Cohen, Omer Gurewitz
In this paper, we study the secrecy rate and outage probability in Multiple-Input-Single-Output (MISO) Gaussian wiretap channels at the limit of a large number of legitimate users…
Opportunistic Scheduling in Heterogeneous Networks: Distributed Algorithms and System Capacity
Joseph Kampeas, Asaf Cohen, Omer Gurewitz
In this work, we design and analyze novel distributed scheduling algorithms for multi-user MIMO systems. In particular, we consider algorithms which do not require sending channel…