Garbage collection optimization for non uniform memory access architectures

Cache-coherent non uniform memory access (ccNUMA) architecture is a standard design pattern for contemporary multicore processors, and future generations of architectures are likely to be NUMA. NUMA architectures create new challenges for managed runtime systems. Memory-intensive applications use the system’s distributed memory banks to allocate data, and the automatic memory manager collects garbage left in these memory banks. The garbage collector may need to access remote memory banks, which entails access latency overhead and potential bandwidth saturation for the interconnection between memory banks. This dissertation makes five significant contributions to garbage collection on NUMA systems, with a case study implementation using the Hotspot Java Virtual Machine. It empirically studies data locality for a Stop-The-World garbage collector when tracing connected objects in NUMA heaps. First, it identifies a locality richness which exists naturally in connected objects that contain a root object and its reachable set— ‘rooted sub-graphs’. Second, this dissertation leverages the locality characteristic of rooted sub-graphs to develop a new NUMA-aware garbage collection mechanism. A garbage collector thread processes a local root and its reachable set, which is likely to have a large number of objects in the same NUMA node. Third, a garbage collector thread steals references from sibling threads that run on the same NUMA node to improve data locality. This research evaluates the new NUMA-aware garbage collector using seven benchmarks of an established real-world DaCapo benchmark suite. In addition, evaluation involves a widely used SPECjbb benchmark and Neo4J graph database Java benchmark, as well as an artificial benchmark. The results of the NUMA-aware garbage collector on a multi-hop NUMA architecture show an average of 15% performance improvement. Furthermore, this performance gain is shown to be as a result of an improved NUMA memory access in a ccNUMA system. Fourth, the existing Hotspot JVM adaptive policy for configuring the number of garbage collection threads is shown to be suboptimal for current NUMA machines. The policy uses outdated assumptions and it generates a constant thread count. In fact, the Hotspot JVM still uses this policy in the production version. This research shows that the optimal number of garbage collection threads is application-specific and configuring the optimal number of garbage collection threads yields better collection throughput than the default policy. Fifth, this dissertation designs and implements a runtime technique, which involves heuristics from dynamic collection behavior to calculate an optimal number of garbage collector threads for each collection cycle. The results show an average of 21% improvements to the garbage collection performance for DaCapo benchmarks.

Towards in silico IBV vaccine design: defining the role of polymorphism in viral attenuation

The gammacoronavirus, Infectious Bronchitis Virus (IBV), is a respiratory pathogen of chickens. IBV is a constant threat to poultry production as established vaccines are often ineffective against emerging strains. This requires constant and rapid vaccine production by a process of viral attenuation by egg passage, but the essential forces leading to attenuation in the virus have not yet been characterised. Knowledge of these factors will lead to the development of more effective, rationally attenuated, live vaccines and reduction of the mortality and morbidity caused by this pathogen. M41 CK strain was egg passaged four times many years ago at Houghton Poultry Research Station and stored as M41-CK EP4 (stock virus at The Pirbright Institute since 1992). It was the first egg passage to have its genome pyrosequenced and was therefore used as the baseline reference. The overall aim of this project was to analyse deep sequence data obtained from four IBV isolates (called A, A1, C and D) each originating from the common M41-CK EP4 (ep4) and independently passaged multiple times in embryonated chicken eggs (figure 1.1). Highly polymorphic encoding regions of the IBV genome were then identified which are likely involved in the attenuation process through the formation of independent SNPs and/or SNP clusters. This was then used to direct targeted investigation of SNPs during the attenuation process of the four IBV passages. A previously generated deep sequence dataset was used as a preliminary map of attenuation for one virulent strain of IBV. This investigation showed the nucleocapsid and spike as two highly polymorphic encoding regions within the IBV genome with the highest proportion of SNPs compared to encoding region size. This analysis then led to more focussed studies of the nucleocapsid and spike encoding region with the ultimate aim of mapping key attenuating regions and nucleotide positions. The 454 pyrosequencing data and further investigation of nucleocapsid and spike encoding regions have identified the SNPs present at the same nucleotide positions within analysed A, A1, C and D isolates. These SNPs probably play a crucial role in viral attenuation and universal vaccine production but it is not clear if independent SNPs are also involved in loss of virulence. The majority of SNPs accumulated at different nucleotide positions without further continuation in Sanger sequenced egg passages presenting S2 subunit (spike) and nucleocapsid as polymorphic encoding regions which in nature remain highly conserved.