Pingfan Meng
Papers
1
Total Citations
17
H-Index
1
About
Pingfan Meng is a researcher whose work lies at the intersection of reconfigurable computing, real-time embedded systems, and hardware acceleration. His most cited paper, "Real-time 3D reconstruction for FPGAs: A case study for evaluating the performance, area, and programmability trade-offs of the Altera OpenCL SDK" (2014, 17 citations), makes a significant contribution by demonstrating how Field-Programmable Gate Arrays (FPGAs) can enable real-time 3D reconstruction from low-cost depth sensors—a task traditionally reliant on powerful GPUs. This work systematically evaluates the trade-offs between performance, chip area, and programmability using the Altera OpenCL SDK, offering crucial insights for deploying augmented reality, mobile robotics, and other latency-sensitive applications on resource-constrained platforms. By showing that FPGAs can achieve comparable or superior performance to GPUs while consuming less power and offering greater flexibility, Meng’s research opens new possibilities for embedded vision systems. His findings are particularly valuable for students and engineers seeking to balance computational efficiency with design complexity in real-time 3D processing, making his work a foundational reference in the field of FPGA-based acceleration.
Research Focus
Key Achievements
Top Papers
- 1