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Found 5 papers, 5 papers with code
HLSFactory: A Framework Empowering High-Level Synthesis Datasets for Machine Learning and Beyond
HLSFactory has three main stages: 1) a design space expansion stage to elaborate single HLS designs into large design spaces using various optimization directives across multiple vendor tools, 2) a design synthesis stage to execute HLS and FPGA tool flows concurrently across designs, and 3) a data aggregation stage for extracting standardized data into packaged datasets for ML usage.
INR-Arch: A Dataflow Architecture and Compiler for Arbitrary-Order Gradient Computations in Implicit Neural Representation Processing
In this work, we introduce INR-Arch, a framework that transforms the computation graph of an nth-order gradient into a hardware-optimized dataflow architecture.
GNNBuilder: An Automated Framework for Generic Graph Neural Network Accelerator Generation, Simulation, and Optimization
Therefore, in this work, we propose GNNBuilder, the first automated, generic, end-to-end GNN accelerator generation framework.
FlowGNN: A Dataflow Architecture for Real-Time Workload-Agnostic Graph Neural Network Inference
First, we propose a novel and scalable dataflow architecture, which generally supports a wide range of GNN models with message-passing mechanism.
GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration
Second, we aim to support a diverse set of GNN models with the extensibility to flexibly adapt to new models.
