Multicore Scalability Through Asynchronous Work
| dc.contributor.author | Mathew, Ajit | en |
| dc.contributor.committeechair | Min, Chang Woo | en |
| dc.contributor.committeemember | Zeng, Haibo | en |
| dc.contributor.committeemember | Lee, Dongyoon | en |
| dc.contributor.department | Electrical and Computer Engineering | en |
| dc.date.accessioned | 2021-07-07T06:00:28Z | en |
| dc.date.available | 2021-07-07T06:00:28Z | en |
| dc.date.issued | 2020-01-13 | en |
| dc.description.abstract | With the end of Moore's Law, computer architects have turned to multicore architecture to provide high performance. Unfortunately, to achieve higher performance, multicores require programs to be parallelized which is an untamed problem. Amdahl's law tells that the maximum theoretical speedup of a program is dictated by the size of the non-parallelizable section of a program. Hence to achieve higher performance, programmers need to reduce the size of sequential code in the program. This thesis explores asynchronous work as a means to reduce sequential portions of program. Using asynchronous work, a programmer can remove tasks which do not affect data consistency from the critical path and can be performed using background thread. Using this idea, the thesis introduces two systems. First, a synchronization mechanism, Multi-Version Read-Log-Update(MV-RLU), which extends Read-Log-Update (RLU) through multi-versioning. At the core of MV-RLU design is a concurrent garbage collection algorithm which reclaims obsolete versions asynchronously reducing blocking of threads. Second, a concurrent and highly scalable index-structure called Hydralist for multi-core. The key idea behind design of Hydralist is that an index-structure can be divided into two component (search layer and data layer) and updates to data layer can be done synchronously while updates to search layer can be propagated asynchronously using background threads. | en |
| dc.description.abstractgeneral | Up until mid-2000s, Moore's law predicted that performance CPU doubled every two years. This is because improvement in transistor technology allowed smaller transistor which can switch at higher frequency leading to faster CPU clocks. But faster clock leads to higher heat dissipation and as chips reached their thermal limits, computer architects could no longer increase clock speeds. Hence they moved to multicore architecture, wherein a single die contains multiple CPUs, to allow higher performance. Now programmers are required to parallelize their code to take advangtage of all the CPUs in a chip which is a non trivial problem. The theoretical speedup achieved by a program on multicore architecture is dictated by Amdahl's law which describes the non parallelizable code in a program as the limiting factor for speedup. For example, a program with 99% parallelizable code can achieve speedup of 20 whereas a program with 50% parallelizable code can only achieve speedup of 2. Therefore to achieve high speedup, programmers need to reduce size of serial section in their program. One way to reduce sequential section in a program is to remove non-critical task from the sequential section and perform the tasks asynchronously using background thread. This thesis explores this technique in two systems. First, a synchronization mechanism which is used co-ordinate access to shared resource called Multi-Version Read-Log-Update (MV-RLU). MV-RLU achieves high performance by removing garbage collection from critical path and performing it asynchronously using background thread. Second, an index structure, Hydralist, which based on the insight that an index structure can be decomposed into two components, search layer and data layer, and decouples updates to both the layer which allows higher performance. Updates to search layer is done synchronously while updates to data layer is done asynchronously using background threads. Evaluation shows that both the systems perform better than state-of-the-art competitors in a variety of workloads. | en |
| dc.description.degree | Master of Science | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:23681 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/104116 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Multicore scalability | en |
| dc.subject | synchonization | en |
| dc.subject | index structures | en |
| dc.subject | databases | en |
| dc.title | Multicore Scalability Through Asynchronous Work | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Computer Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | Master of Science | en |
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