Kai-Cheung Leung

University of Otago · Department of Computer Science

K Nearest Neighbors (k-NN) search is a widely used category of algorithms with applications in domains such as computer vision and machine learning. With the rapidly increasing amount of data available, and their high dimensionality, k-NN algorithms scale poorly on multicore systems because they hit a memory wall. In this paper, we propose a novel...

This paper extensively evaluates the performance of View-Oriented Transactional Memory (VOTM) based on two implementations that adopt different Transactional Memory (TM) algorithms. The Restricted Admission Control (RAC) mechanism in VOTM plays a key role in the performance gains of VOTM. In this paper, we use six applications to evaluate the perfo...

In memory-intensive algorithms, the problem size is often so large that it cannot fit into the cache of a CPU, and this may result in an excessive number of cache misses, a bottleneck that can easily make seemingly embarrassingly-parallel algorithms such as feature-matching unscalable in many core systems. To solve this bottleneck, this paper propo...

Feature matching is a fundamental problem in many computer vision tasks. As datasets become larger, and individual image resolution increases, this is becoming more and more computationally demanding work. While prior knowledge about the scene geometry can, in some cases, reduce the number of image pairs that need to be considered, the sheer volume...

Many computer vision applications are entering the 'big data' era: it is straightforward to acquire very large datasets that need to be processed. Our current research targets a large-scale structure-from-motion application, in which 3D models are formed from large collections of digital photographs. There have also been many recent technological d...

Parallel programming is the mainstream for today's HPC applications. Programmers need to parallelize their programs to achieve better performance on multicore systems. However, due to a lack of good understanding of parallelism in algorithms, scheduling policy in runtime systems, and multicore architectures, programmers usually find it very hard to...

This paper proposes a Restricted Admission Control (RAC) scheme for View-Oriented Transactional Memory. The scheme can control the number of threads concurrently accessing a view in order to reduce the number of aborts of transactions. The RAC scheme has the merits of both the locking mechanism and the transactional memory. A theoretical model is p...

This paper extends the Restricted Admission Control (RAC) theoretical model to cover the multiple-view cases in View-Oriented Transactional Memory (VOTM) to analyze potential performance gain in VOTM when shared data is partitioned into multiple views. Experimental results show that partitioning shared data into separate views, each of which is ind...

This paper proposes the View-Oriented Transactional Memory (VOTM) model to seamlessly integrate locking mechanism and transactional memory. The VOTM model allows programmers to partition the shared memory into "views", which are non-overlapping sets of shared data objects. The Restricted Admission Control (RAC) scheme can then control the number of...

In this paper, we have further explored the novel metrics and policies of Speedup per Watt (SPW), Power per Speedup (PPS), Energy per Target (EPT), Sharing Policy, the Hare and the Tortoise Policies, which were introduced in our previous work. Each policy leverages application parallelism and Dynamic Voltage and Frequency Scaling (DVFS) to reduce e...

This paper proposes a scheme for automatic detection of view access in the View-Oriented Parallel Programming (VOPP) model. VOPP is a shared-memory-based, data-centric model that uses “views” to bundle mutual exclusion with data access. Based on the automatic detection scheme, a view is automatically acquired when first accessed, and automatically...

In this paper, we have proposed three new metrics, Speedup per Watt (SPW), Power per Speedup (PPS) and Energy per Target (EPT), to guide task schedulers to select the best task schedules for energy saving in multicore computers. Based on these metrics, we have proposed the novel Sharing Policies, the Hare and the Tortoise Policies, which have taken...

Data races hamper parallel programming and threaten the reliability of future software. This paper proposes the data race prevention scheme View-Oriented Data race Prevention (VODAP), which can prevent data races in the View-Oriented Parallel Programming (VOPP) model. VOPP is a novel shared-memory data-centric parallel programming model, which uses...

This paper proposes a data race prevention scheme, which can prevent data races in the View-Oriented Parallel Programming (VOPP) model. VOPP is a novel shared-memory data-centric parallel programming model, which uses views to bundle mutual exclusion with data access. We have implemented the data race prevention scheme with a memory protection mech...

The University of Otago submitted three element runs and three passage runs to the Relevance-in-Context task of the ad hoc track. The best Otago run was a whole-document run placing 7 th . The best Otago passage run placed 13 th while the best Otago element run placed 31 st . There were a total of 40 runs submitted to the task. The ad hoc result re...

Myostatin is a member of the TGF-beta superfamily and is primarily known for its ability to inhibit muscle growth. It also has actions on glucose metabolism. We hypothesized that it may act as a paracrine regulator of glucose uptake in the placenta, potentially contributing to fetal and placental growth. The objective of this study was to determine...