6 citations · 11 across the 9 of their papers we have counts for
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Exploring Memory Access Patterns for Graph Processing Accelerators
Jonas Dann, Daniel Ritter, Holger Fröning
Recent trends in business and technology (e.g., machine learning, social network analysis) benefit from storing and processing growing amounts of graph-structured data in databases…
On Resource-Efficient Bayesian Network Classifiers and Deep Neural Networks
Wolfgang Roth, Günther Schindler, Holger Fröning +1
We present two methods to reduce the complexity of Bayesian network (BN) classifiers. First, we introduce quantization-aware training using the straight-through gradient estimator…
Resource-Efficient Speech Mask Estimation for Multi-Channel Speech Enhancement
Lukas Pfeifenberger, Matthias Zöhrer, Günther Schindler +3
While machine learning techniques are traditionally resource intensive, we are currently witnessing an increased interest in hardware and energy efficient approaches. This need for…
Non-Relational Databases on FPGAs: Survey, Design Decisions, Challenges
Jonas Dann, Daniel Ritter, Holger Fröning
Non-relational database systems (NRDS), such as graph, document, key-value, and wide-column, have gained much attention in various trending (business) application domains like smar…
On the Difficulty of Designing Processor Arrays for Deep Neural Networks
Kevin Stehle, Günther Schindler, Holger Fröning
Systolic arrays are a promising computing concept which is in particular inline with CMOS technology trends and linear algebra operations found in the processing of artificial neur…
A Simple Model for Portable and Fast Prediction of Execution Time and Power Consumption of GPU Kernels
Lorenz Braun, Sotirios Nikas, Chen Song +2
Characterizing compute kernel execution behavior on GPUs for efficient task scheduling is a non-trivial task. We address this with a simple model enabling portable and fast predict…