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The popularity of GPU programming languages that explicitly express thread-level parallelism leads to the question of whether they can also be used for programming reconfigurable accelerators. This paper describes Guppy, a GPU-like softcore processor based on the in-order LEON3 core. Our long-term vision is to have a unified programming paradigm for accelerators - regardless of whether they are FPGA or GPU based. While others have explored this from a high level hardware synthesis perspective, we chose to adopt the approach of a parametrically reconfigurable softcore. We will discuss the main architecture features of Guppy, compare its performance to the original core. Our design has been synthesized on a Xilinx Virtex 5 FPGA.