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Graphics Processing Units (GPUs) have found application in a broad range of domains due to their ability to massively exploit data parallelism and thereby achieve high energy efficiency, being now referred to as General-Purpose GPUs (GPGPUs). However, with a market dominated by two or three industrial players and a lack of open-source hardware realizations and standardized GPU Instruction-Set Architectures (ISAs), the full potential of these architectures for academic research and use by small hardware development enterprises remains far from being unlocked. In this paper, we start by discussing a few exciting research directions in GPGPU architectures and the benefits of open-source Hardware realizations. Furthermore, we show how our open-source FGPU core can be used to enable overcoming these challenges and contribute to the agile development of Domain-Specific Architectures (DSAs) featuring System-on-Chip (SoC) platforms extended with adapted GPGPU cores. FGPU is described in VHDL, can be programmed in OpenCL by use of our LLVM-based compiler, and has been validated against an ARM Cortex A9 with NEON support, achieving 4 performance improvement in fixed and floating-point benchmarks.

(Special Topic Submission) enabling domain-specific architectures with an open-source soft-core GPGPU / Brandalero, M.; Hernandez, H. G. M.; Veleski, M.; Kadi, M. A.; Rech, P.; Hubner, M.. - (2020), pp. 36-43. ((Intervento presentato al convegno 34th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020 tenutosi a usa nel 2020 [10.1109/IPDPSW50202.2020.00015].

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