In order to meet the increased computational demands and stricter power constraints of modern applications, architectures have evolved to include domain-specific dedicated accelerators. In order to design efficient accelerators, three main components need to be addressed: compute, memory, and control. Moreover, since SoCs usually contain multiple accelerators, selecting the right one for each task also become crucial. This becomes specially […]

science with practical applications ranging from pattern matching to computational biology. The ever-increasing volumes of genomic data produced by modern DNA sequencers motivate improved software and hardware sequence alignment accelerators that scale with longer sequence lengths and high error rates without losing accuracy. Furthermore, the wide variety of use cases requiring sequence alignment demands flexible and efficient solutions that can […]

Energy-efficient execution of task-based parallel applications is crucial as tasking is a widely supported feature in many parallelprogramming libraries and runtimes. Currently, state-of-the-art proposals primarily rely on leveraging core asymmetry and CPUDVFS. Additionally, these proposals mostly use heuristics and lack the ability to explore the trade-offs between energy usage andperformance. However, our findings demonstrate that focusing solely on CPU energy […]

The eProcessor project aims at creating a RISC-V full stack ecosystem. The eProcessor architecture combines a high-performance out-of-order core with energy-efficient accelerators for vector processing and artificial intelligence with reduced-precision functional units. The design of this architecture follows a hardware/software co-design approach with relevant application use cases from the high-performance computing, bioinformatics and artificial intelligence domains. Two eProcessor prototypes will […]