Search Results for author: Dionysios Diamantopoulos

Found 2 papers, 0 papers with code

LEAPER: Fast and Accurate FPGA-based System Performance Prediction via Transfer Learning

no code implementations22 Aug 2022 Gagandeep Singh, Dionysios Diamantopoulos, Juan Gómez-Luna, Sander Stuijk, Henk Corporaal, Onur Mutlu

The key idea of LEAPER is to transfer an ML-based performance and resource usage model trained for a low-end edge environment to a new, high-end cloud environment to provide fast and accurate predictions for accelerator implementation.

Design Synthesis Transfer Learning

Agile Autotuning of a Transprecision Tensor Accelerator Overlay for TVM Compiler Stack

no code implementations20 Apr 2020 Dionysios Diamantopoulos, Burkhard Ringlein, Mitra Purandare, Gagandeep Singh, Christoph Hagleitner

Specialized accelerators for tensor-operations, such as blocked-matrix operations and multi-dimensional convolutions, have been emerged as powerful architecture choices for high-performance Deep-Learning computing.

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