VLDB 2026 Research / reviewers in the wild / expert
Bo-Yi Huang
dblp:175/6139
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
GPUs and heterogeneous computing · 50% Performance modeling and evaluation · 50% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Performance modeling and evaluation › simulation
monte carlo simulation |
0.2 | 1 | 2016 | A Platform-Oblivious Approach for Heterogeneous Computing: A Case Study with Monte Carlo-based Simulation for Medical Applications · FPGA 2016 |
GPUs and heterogeneous computing › heterogeneous programming models
OpenCL |
0.2 | 1 | 2016 | A Platform-Oblivious Approach for Heterogeneous Computing: A Case Study with Monte Carlo-based Simulation for Medical Applications · FPGA 2016 |
Medical and health informatics
medical simulation |
0.1 | 1 | 2016 | A Platform-Oblivious Approach for Heterogeneous Computing: A Case Study with Monte Carlo-based Simulation for Medical Applications · FPGA 2016 |
Methods — techniques the papers use, named apart from their topics
monte carlo · 0.5OpenCL · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | A Platform-Oblivious Approach for Heterogeneous Computing: A Case Study with Monte Carlo-based Simulation for Medical ApplicationsabstractLight is important and helpful in many medical applications, such as cancer treatment. Computer modeling and simulation of light transport are often adopted to improve the quality of medical treatments. In particular, Monte Carlo-based simulations are considered to deliver accurate results, but require intensive computational resources. While several attempts to accelerate the Monte Carlo-based methods for the simulation of photon transport with platform-specific programming schemes, such as CUDA on GPU and HDL on FPGA, have been proposed, the approach has limited portability and prolongs software updates. In this paper, we parallelize the Monte Carlo modeling of light transport in multi-layered tissues (MCML) program with OpenCL, an open standard supported by a wide range of platforms. We characterize the performance of the parallelized MCML kernel program runs on CPU, GPU and FPGA. Compared to platform-specific programming schemes, our platform-oblivious approach provides a unified, highly portable code and delivers competitive performance and power efficiency. Shih-Hao Hung, Min-Yu Tsai, Bo-Yi Huang, Chia-Heng Tu |
FPGA | 3 |