Papers
1
Total Citations
6
H-Index
1
About
Jinyi Xu is a researcher whose work focuses on the intersection of computer architecture and high-performance computing, particularly the efficient scheduling of tasks in multicore systems integrated with hardware accelerators. His most cited paper, "Efficient tasks scheduling in multicore systems integrated with hardware accelerators" (2022), tackles the critical challenge of optimizing workload distribution between general-purpose cores and specialized accelerators to maximize throughput and energy efficiency. This contribution is especially relevant as heterogeneous computing becomes central to modern processors, from data centers to edge devices. With 6 citations, this work has already drawn attention from peers seeking practical solutions for real-time and resource-constrained environments. Xu’s research is notable for its emphasis on balancing computational demands with hardware capabilities, a key enabler for next-generation systems in AI, scientific computing, and embedded applications. His achievements reflect a growing impact in the field, positioning him as a promising voice in the ongoing evolution of multicore and accelerator-based architectures.
Research Focus
Key Achievements
Top Papers
- 1