483 citations · 523 across the 7 of their papers we have counts for
8 papers
SMaRTT: Sender-based Marked Rapidly-adapting Trimmed & Timed Transport
Tommaso Bonato, Abdul Kabbani, Ahmad Ghalayini +10
With the rapid growth of artificial intelligence (AI) workloads in datacenters, the Ultra Ethernet Consortium (UEC) has defined a new high-performance transport layer to deliver th…
Demystifying Chains, Trees, and Graphs of Thoughts
Maciej Besta, Florim Memedi, Zhenyu Zhang +13
The field of natural language processing (NLP) has witnessed significant progress in recent years, with a notable focus on improving large language models' (LLM) performance throug…
HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers
Maciej Besta, Afonso Claudino Catarino, Lukas Gianinazzi +4
Many graph representation learning (GRL) problems are dynamic, with millions of edges added or removed per second. A fundamental workload in this setting is dynamic link prediction…
A High-Performance Design, Implementation, Deployment, and Evaluation of The Slim Fly Network
Nils Blach, Maciej Besta, Daniele De Sensi +10
Novel low-diameter network topologies such as Slim Fly (SF) offer significant cost and power advantages over the established Fat Tree, Clos, or Dragonfly. To spearhead the adoption…
Graph of Thoughts: Solving Elaborate Problems with Large Language Models
Maciej Besta, Nils Blach, Ales Kubicek +8
We introduce Graph of Thoughts (GoT): a framework that advances prompting capabilities in large language models (LLMs) beyond those offered by paradigms such as Chain-of-Thought or…
The Graph Database Interface: Scaling Online Transactional and Analytical Graph Workloads to Hundreds of Thousands of Cores
Maciej Besta, Robert Gerstenberger, Marc Fischer +9
Graph databases (GDBs) are crucial in academic and industry applications. The key challenges in developing GDBs are achieving high performance, scalability, programmability, and po…
PolarStar: Expanding the Scalability Horizon of Diameter-3 Networks
Kartik Lakhotia, Laura Monroe, Kelly Isham +4
We present PolarStar, a novel family of diameter-3 network topologies derived from the star product of low-diameter factor graphs. PolarStar gives the largest known diameter-3 netw…
EvalNet: A Practical Toolchain for Generation and Analysis of Extreme-Scale Interconnects
Maciej Besta, Patrick Iff, Marcel Schneider +10
The diversity of communication paths in a network, especially non-minimal paths, is a key enabler of performance at extreme scales. We present EvalNet, a toolchain for scalable gen…