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06/27/2023
CARMA: Context-Aware Runtime Reconfiguration for Energy-Efficient Sensor Fusion
Autonomous systems (AS) are systems that can adapt and change their beha...
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04/11/2023
Late Breaking Results: Scalable and Efficient Hyperdimensional Computing for Network Intrusion Detection
Cybersecurity has emerged as a critical challenge for the industry. With...
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04/11/2023
DistHD: A Learner-Aware Dynamic Encoding Method for Hyperdimensional Classification
Brain-inspired hyperdimensional computing (HDC) has been recently consid...
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01/16/2023
PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks
Relational graph neural networks (RGNNs) are graph neural networks (GNNs...
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09/07/2022
Sgap: Towards Efficient Sparse Tensor Algebra Compilation for GPU
Sparse compiler is a promising solution for sparse tensor algebra optimi...
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07/03/2022
Chimera: A Hybrid Machine Learning Driven Multi-Objective Design Space Exploration Tool for FPGA High-Level Synthesis
In recent years, hardware accelerators based on field-programmable gate ...
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03/04/2021
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture
Graph Convolutional Networks (GCNs) are increasingly adopted in large-sc...
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03/02/2021
Mind Mappings: Enabling Efficient Algorithm-Accelerator Mapping Space Search
Modern day computing increasingly relies on specialization to satiate gr...
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01/20/2021
PyTorch-Direct: Enabling GPU Centric Data Access for Very Large Graph Neural Network Training with Irregular Accesses
With the increasing adoption of graph neural networks (GNNs) in the mach...
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08/04/2019
Analysis and Optimization of I/O Cache Coherency Strategies for SoC-FPGA Device
Unlike traditional PCIe-based FPGA accelerators, heterogeneous SoC-FPGA ...
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04/09/2019
FPGA/DNN Co-Design: An Efficient Design Methodology for IoT Intelligence on the Edge
While embedded FPGAs are attractive platforms for DNN acceleration on ed...
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06/17/2017