Towards “True” GPU Performance Scaling for OpenGPU

General-Purpose Graphics Processing Units (GPGPUs) have gained significant attention for their high computational throughput and energy efficiency. Their ability to offer high-performance, general-purpose programmability makes them ideal for accelerating diverse applications in fields such as artificial intelligence, scientific computing, healthcare, financial modeling, and computer graphics. The Vortex OpenGPU introduced the first open-source full-system GPGPU, extending the RISC-V base ISA to introduce a Single-Instruction-Multiple-Threads (SIMT) execution model. In this work, we extended the OpenGPU microarchitecture into a configurable superscalar pipeline, migrating it from a CPU-oriented microarchitecture - where the performance scaling was centered on increasing the number of GPU cores - to a GPU-oriented microarchitecture where the performance scaling is centered towards scaling the parallelism inside a single core. We evaluated the design on Intel FPGA, achieving a 29% performance increase with a 4 -wide single-core 32 threads GPU versus an areaequivalent 16-core processor.