44 citations · 139 across the 12 of their papers we have counts for
14 papers
Arithmetic Packing on Wide Integer Datapaths in DSP Primitives of Modern FPGA Devices
Titus Bornträger, Shane Fleming, Philipp Holzinger +3
Deep Neural Networks increasingly employ low-precision quantization to reduce computational requirements. While FPGAs are well suited for workloads with heterogeneous precisions, t…
SIRA: Scaled-Integer Range Analysis for Optimizing FPGA Dataflow Neural Network Accelerators
Yaman Umuroglu, Christoph Berganski, Felix Jentzsch +8
While neural network quantization effectively reduces the cost of matrix multiplications, aggressive quantization can expose non-matrix-multiply operations as significant performan…
FINN-GL: Generalized Mixed-Precision Extensions for FPGA-Accelerated LSTMs
Shashwat Khandelwal, Jakoba Petri-Koenig, Thomas B. Preußer +2
Recurrent neural networks (RNNs), particularly LSTMs, are effective for time-series tasks like sentiment analysis and short-term stock prediction. However, their computational comp…
Shedding the Bits: Pushing the Boundaries of Quantization with Minifloats on FPGAs
Shivam Aggarwal, Hans Jakob Damsgaard, Alessandro Pappalardo +4
Post-training quantization (PTQ) is a powerful technique for model compression, reducing the numerical precision in neural networks without additional training overhead. Recent wor…
Understanding and Fixing Complex Faults in Embedded Cyberphysical Systems
Alexander Weiss, Smitha Gautham, Athira Varma Jayakumar +4
Understanding fault types can lead to novel approaches to debugging and runtime verification. Dealing with complex faults, particularly in the challenging area of embedded systems,…
MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions
Wenqi Jiang, Zhenhao He, Shuai Zhang +9
Deep neural networks are widely used in personalized recommendation systems. Unlike regular DNN inference workloads, recommendation inference is memory-bound due to the many random…
HyperLogLog Sketch Acceleration on FPGA
Amit Kulkarni, Monica Chiosa, Thomas B. Preußer +3
Data sketches are a set of widely used approximated data summarizing techniques. Their fundamental property is sub-linear memory complexity on the input cardinality, an important a…
Using DSP Slices as Content-Addressable Update Queues
Thomas B. Preußer, Monica Chiosa, Alexander Weiss +1
Content-Addressable Memory (CAM) is a powerful abstraction for building memory caches, routing tables and hazard detection logic. Without a native CAM structure available on FPGA d…
Optimizing Bit-Serial Matrix Multiplication for Reconfigurable Computing
Yaman Umuroglu, Davide Conficconi, Lahiru Rasnayake +2
Matrix-matrix multiplication is a key computational kernel for numerous applications in science and engineering, with ample parallelism and data locality that lends itself well to…
FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks
Michaela Blott, Thomas Preusser, Nicholas Fraser +3
Convolutional Neural Networks have rapidly become the most successful machine learning algorithm, enabling ubiquitous machine vision and intelligent decisions on even embedded comp…
Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic
Michaela Blott, Thomas B. Preusser, Nicholas Fraser +4
Convolutional Neural Networks have dramatically improved in recent years, surpassing human accuracy on certain problems and performance exceeding that of traditional computer visio…
Generic and Universal Parallel Matrix Summation with a Flexible Compression Goal for Xilinx FPGAs
Thomas B. Preußer
Bit matrix compression is a highly relevant operation in computer arithmetic. Essentially being a multi-operand addition, it is the key operation behind fast multiplication and man…
Inference of Quantized Neural Networks on Heterogeneous All-Programmable Devices
Thomas B. Preußer, Giulio Gambardella, Nicholas Fraser +1
Neural networks have established as a generic and powerful means to approach challenging problems such as image classification, object detection or decision making. Their successfu…
QBM - Mapping User-Specified Functions to Programmable Logic through a QBF Satisfiability Problem
Thomas B. Preußer
This is a brief overview on the background behind the test set formulas generated by the QBM tool. After establishing its application context, its formal approach to the generation…