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Research and Publication

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Research Overview

Bingsheng is leading Xtra Computing Group. It is a small group of students and researchers in Singapore, who have been building various computing systems. Xtra's mission is to build faster, greener and cheaper high performance systems. With the passion in system research, Bingsheng strongly believes in prototype implementation and empirical evaluation in addition to theoretical formalization and algorithmic design. As a result, his group and collaborators have developed a number of system prototypes (including Medusa, OmniDB, Mars and FD-tree) that are often requested and used by other researchers. Bingsheng's current research interests range from bare metal hardware-software co-design to distributed systems for massive data processing.

Past Projects

Here are some examples of past projects:

medusa Medusa (2010-2015): It is the first system of its kind in Building GPU-based Parallel Sparse Graph Applications with Sequential C/C++ Code. Medusa offers a small set of user-defined APIs, and embraces a runtime system to automatically execute those APIs in parallel on the GPUs. We further develop a series of graph-centric optimizations based on the architecture features of GPU for efficiency. Additionally, Medusa is extended to execute on multiple GPUs within a machine or a cluster. Our empirical studies demonstrate the programmability and efficiency of Medusa for a series of common graph operations. See [TPDS13] [VLDB13BestDemo]

Omnidb OmniDB (2011-2015): Relational databases on emerging many-core architectures (including many-core CPUs, GPUs and APUs) Here are some highlights: a) OmniDB proposes a kernel-adapter based design, a portable yet efficient query processor on parallel CPU/GPU architectures [VLDB13Demo]. b) Two novel designs for taking advange of coupled CPU-GPU architectures (e.g., APUs) [VLDB2013] [VLDB2015]. c) GPL: a pipeline query execution engine [SIGMOD2016].

fpga ReconfigDB (2013-2016): Hardware-software system design on OpenCL-based FPGAs The vision is to develop bionic parallel systems (e.g., database systems) with superb hardware speed (aka. bare-matal). To achieve this abitious goal, we need novel tools and systems. Example tools: we leverage static and dynamic analysis to develop an analytical performance model, which has captured the key architectural features of FPGA abstractions under OpenCL [HPCA16]. Example systems: databases [FPL2016], graph processing [ongoing].

Current Projects

Here are some examples of current projects:


This project develops the next-generation of event stream processing engines. The key motivation is from the big event streams generated by IoT devices.

See our publications: BrickStream profiling and benchmark of streaming engines


This project researches the novel design and implementation of graph accelerators. Due to the complexity of graph processing, the performance and energy efficiency of graph accelerators have been an interesting research topic.

See our publications: Survey Novel conflict handling graph engine on FPGA


This project examines the design and implementation of machine learning systems under new environments, such as hardware accelerations and federated machine learning.

See our publications/systems: hardware accelerations (ThunderSVM and ThunderGBM), and federated machine learning systems (Survey).


My publication list: Entry@DBLP Google scholar

Our open-sourced systems can be found at Xtra group Github site.

Selected Publications

Pioneering data management on emerging processors (GPUs/FPGAs).

From GPUs/FPGAs to full-stacked hardware systems

From databases to other data management

From single-machine to distributed computing/cloud

Machine learning systems

This is partial list of awards obtained by Xtra's members.

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