Publications (21)
Neural Graph Databases
Maciej Besta, Patrick Iff, Florian Scheidl +5
Graph databases (GDBs) enable processing and analysis of unstructured, complex, rich, and usually vast graph datasets. Despite the large significance of GDBs in both academia and i…
FoldedHexaTorus: An Inter-Chiplet Interconnect Topology for Chiplet-based Systems using Organic and Glass Substrates
Patrick Iff, Maciej Besta, Torsten Hoefler
Chiplet-based systems are rapidly gaining traction in the market. Two packaging options for such systems are the established organic substrates and the emerging glass substrates. T…
RapidChiplet: A Toolchain for Rapid Design Space Exploration of Chiplet Architectures
Patrick Iff, Benigna Bruggmann, Blaise Morel +3
Chiplet architectures are on the rise as they promise to overcome the scaling challenges of monolithic chips. A key component of such architectures is an efficient inter-chiplet in…
Psychologically Enhanced AI Agents
Maciej Besta, Shriram Chandran, Robert Gerstenberger +9
We introduce MBTI-in-Thoughts, a framework for enhancing the effectiveness of Large Language Model (LLM) agents through psychologically grounded personality conditioning. Drawing o…
EvalNet: A Practical Toolchain for Generation and Analysis of Extreme-Scale Interconnects
Maciej Besta, Patrick Iff, Marcel Schneider +10
EvalNet is a practical toolchain that generates and analyzes a wide range of extreme‑scale network topologies, providing detailed metrics on shortest and non‑shortest path diversit…
Near-Optimal Wafer-Scale Reduce
Piotr Luczynski, Lukas Gianinazzi, Patrick Iff +3
Efficient Reduce and AllReduce communication collectives are a critical cornerstone of high-performance computing (HPC) applications. We present the first systematic investigation…
ProbGraph: High-Performance and High-Accuracy Graph Mining with Probabilistic Set Representations
Maciej Besta, Cesare Miglioli, Paolo Sylos Labini +11
Important graph mining problems such as Clustering are computationally demanding. To significantly accelerate these problems, we propose ProbGraph: a graph representation that enab…
Higher-Order Graph Databases
Maciej Besta, Shriram Chandran, Jakub Cudak +6
Recent advances in graph databases (GDBs) have been driving interest in large-scale analytics, yet current systems fail to support higher-order (HO) interactions beyond first-order…
Reasoning Language Models: A Blueprint
Maciej Besta, Julia Barth, Eric Schreiber +16
Reasoning language models (RLMs), also known as Large Reasoning Models (LRMs), such as OpenAI's o1 and o3, DeepSeek-R1, and Alibaba's QwQ, have redefined AI's problem-solving capab…
PolarFly: A Cost-Effective and Flexible Low-Diameter Topology
Kartik Lakhotia, Maciej Besta, Laura Monroe +4
In this paper we present PolarFly, a diameter-2 network topology based on the Erdos-Renyi family of polarity graphs from finite geometry. This is a highly scalable low-diameter top…
Inductive Loop Analysis for Practical HPC Application Optimization
Philipp Schaad, Tal Ben-Nun, Patrick Iff +1
Scientific computing applications heavily rely on multi-level loop nests operating on multidimensional arrays. This presents multiple optimization opportunities from exploiting par…
Sparse Hamming Graph: A Customizable Network-on-Chip Topology
Patrick Iff, Maciej Besta, Matheus Cavalcante +3
Chips with hundreds to thousands of cores require scalable networks-on-chip (NoCs). Customization of the NoC topology is necessary to reach the diverse design goals of different ch…
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…
Affordable AI Assistants with Knowledge Graph of Thoughts
Maciej Besta, Lorenzo Paleari, Jia Hao Andrea Jiang +15
Large Language Models (LLMs) are revolutionizing the development of AI assistants capable of performing diverse tasks across domains. However, current state-of-the-art LLM-driven a…
PlaceIT: Placement-based Inter-Chiplet Interconnect Topologies
Patrick Iff, Benigna Bruggmann, Maciej Besta +2
2.5D integration technology is gaining traction as it copes with the exponentially growing design cost of modern integrated circuits. A crucial part of a 2.5D stacked chip is a low…
Network Design for Wafer-Scale Systems with Wafer-on-Wafer Hybrid Bonding
Patrick Iff, Tommaso Bonato, Maciej Besta +2
Transformer-based large language models are increasingly constrained by data movement as communication bandwidth drops sharply beyond the chip boundary. Wafer-scale integration usi…
HexaMesh: Scaling to Hundreds of Chiplets with an Optimized Chiplet Arrangement
Patrick Iff, Maciej Besta, Matheus Cavalcante +3
2.5D integration is an important technique to tackle the growing cost of manufacturing chips in advanced technology nodes. This poses the challenge of providing high-performance in…
Multi-Head RAG: Solving Multi-Aspect Problems with LLMs
Maciej Besta, Ales Kubicek, Robert Gerstenberger +13
Retrieval-Augmented Generation (RAG) improves Large Language Models (LLMs) by retrieving supporting documents into the prompt, but existing methods do not explicitly target queries…
CheckEmbed: Effective Verification of LLM Solutions to Open-Ended Tasks
Maciej Besta, Lorenzo Paleari, Marcin Copik +9
Large Language Models (LLMs) are transforming a wide range of domains, yet verifying their outputs remains a significant challenge, especially for complex open-ended tasks such as…
Hardware Acceleration for Knowledge Graph Processing: Challenges & Recent Developments
Maciej Besta, Robert Gerstenberger, Patrick Iff +9
Knowledge graphs (KGs) have achieved significant attention in recent years, particularly in the area of the Semantic Web as well as gaining popularity in other application domains…
Benchmarking Filtered Approximate Nearest Neighbor Search Algorithms on Transformer-based Embedding Vectors
Patrick Iff, Paul Bruegger, Marcin Chrapek +3
Advances in embedding models for text, image, audio, and video drive progress across multiple domains, including retrieval-augmented generation, recommendation systems, and others.…