activity
20222024
most citedSparseP: Towards Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Systems

2 citations · 3 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CV2024

Low-Bitwidth Floating Point Quantization for Efficient High-Quality Diffusion Models

Cheng Chen, Christina Giannoula, Andreas Moshovos

Diffusion models are emerging models that generate images by iteratively denoising random Gaussian noise using deep neural networks. These models typically exhibit high computation…

cs.AR2024

Evaluating the Effectiveness of Microarchitectural Hardware Fault Detection for Application-Specific Requirements

Konstantinos-Nikolaos Papadopoulos, Christina Giannoula, Nikolaos-Charalampos Papadopoulos +3

Reliability is necessary in safety-critical applications spanning numerous domains. Conventional hardware-based fault tolerance techniques, such as component redundancy, ensure rel…

cs.DC2024

SmartPQ: An Adaptive Concurrent Priority Queue for NUMA Architectures

Christina Giannoula, Foteini Strati, Dimitrios Siakavaras +2

Concurrent priority queues are widely used in important workloads, such as graph applications and discrete event simulations. However, designing scalable concurrent priority queues…

cs.CR2024

Proteus: Preserving Model Confidentiality during Graph Optimizations

Yubo Gao, Maryam Haghifam, Christina Giannoula +3

Deep learning (DL) models have revolutionized numerous domains, yet optimizing them for computational efficiency remains a challenging endeavor. Development of new DL models typica…

cs.LG20231 cited

The Synergy of Speculative Decoding and Batching in Serving Large Language Models

Qidong Su, Christina Giannoula, Gennady Pekhimenko

Large Language Models (LLMs) like GPT are state-of-the-art text generation models that provide significant assistance in daily routines. However, LLM execution is inherently sequen…

cs.AR2023

Architectural Support for Efficient Data Movement in Disaggregated Systems

Christina Giannoula, Kailong Huang, Jonathan Tang +4

Resource disaggregation offers a cost effective solution to resource scaling, utilization, and failure-handling in data centers by physically separating hardware devices in a serve…