CPE: a parallel library for financial engineering applications

Leong, M.-P.; Cheung, Chi-Chiu; Cheung, Chin-Wang; Wan, P.P.M.; Leung, I.K.H.; Yeung, W.M.M.; Yuen, Wing-Seung; Chow, Ka-Po; Leung, K. C.; Leong, Philip H. W.

doi:10.1109/mc.2005.337

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…The parallel calculations can possibly yield results in few seconds for a portfolio instead of ten of minutes without parallelism. Explorations of parallel techniques to reduce response time for such calculations are many [2,11]. As to the previous example on the processing time for pricing the American option of an asset portfolio with 5 entries, the job took about 380 seconds on a single processor, but only took about 16 seconds on a SGI Origin with 32 processors [2].…”

Section: Numerical Simulations In Capital Marketsmentioning

confidence: 99%

Resource management with stateful support for analytic applications

Fong¹,

Crawford²,

Shaikh³

2006

Proceedings 20th IEEE International Parallel &Amp; Distributed Processing Symposium

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Analytic applications from various industrial sectors have specific attributes and requirements including relatively long processing time, parallelization, multiple interactive invocations, web services, and expected quality of service objectives. Current parallel resource management systems for batch-oriented jobs lack the effective support for multiple interactive invocations with consideration in quality of service objectives, while transaction processing systems do not support dynamic creation of parallel application instances. To better serve the analytic applications, a set of additional resource management services, defined as stateful support, introduces the concept of Service Instance and Service Instance Management. This set of stateful support services can be implemented as extension to existing parallel resource management to serve these analytic applications that rapidly increase in the demand of computing power.

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Section: Numerical Simulations In Capital Marketsmentioning

confidence: 99%

Resource management with stateful support for analytic applications

Fong¹,

Crawford²,

Shaikh³

2006

Proceedings 20th IEEE International Parallel &Amp; Distributed Processing Symposium

View full text Add to dashboard Cite

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A high performance pair trading application

Wang

Rostoker

Wagner

2009

2009 IEEE International Symposium on Parallel &Amp; Distributed Processing

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Trace-Based Dynamic Binary Parallelization

Yang¹

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With the number of cores increasing rapidly but the performance per core increasing slowly at best, software must be parallelized in order to improve performance. Manual parallelization is often prohibitively time-consuming and error-prone (especially due to data races and memory-consistency complexities), and some portions of code may simply be too difficult to understand or refactor for parallelization. Most existing automatic parallelization techniques are performed statically at compile time and require source code to be analyzed, leaving a large fraction of software behind.In many cases, some or all of the source code and development tool chain is lost or, in the case of third-party software, was never available. Furthermore, modern applications are assembled and defined at run time, making use of shared libraries, virtual functions, plugins, dynamically-generated code, and other dynamic mechanisms, as well as multiple languages. All these aspects of separate compilation prevent the compiler from obtaining a holistic view of the program, leading to the risk of incompatible parallelization techniques, subtle data races, and resource over-subscription. All the above considerations motivate dynamic binary parallelization (DBP).This dissertation explores the novel idea of trace-based DBP, which provides a large instruction window without introducing spurious dependencies. We hypothesize that traces provide a generally good trade-off between code visibility and analysis accuracy for a wide variety of applications so as to achieve better parallel performance. Compared to the raw dynamic instruction stream (DIS), traces expose more distant parallelism opportunities because their average length is typically much larger than the size of the hardware instruction window. Compared to the complete control flow graph (CFG), traces only contain control and data dependencies on the execution path which is actually taken. More importantly, while DIS-based DBP typically only exploits fine-grained parallelism and CFG-based DBP typically only exploits coarse-grained parallelism, traces can be used as a unified representation of program execution to seamlessly incorporate the exploitation of both coarse-and fine-grained parallelism.We develop Tracy, an innovative DBP framework which monitors a program at run time and i Abstract ii dynamically identifies hot traces, parallelizes them, and caches them for later use so that the program can run in parallel every time a hot trace repeats. Our experimental results have demonstrated that for floating point benchmarks, Tracy can achieve an average speedup of 2.16x, 1.51x better than the speedup achieved by Core Fusion, one representative of DIS-based DBP techniques. Although the average speedup achieved by Tracy is only 1.04x better than the speedup achieved by CFG-based DBP, Tracy can speed up all floating point benchmarks while CFG-based DBP fails to parallelize three out of eight applications at all. The performance of Tracy is not always better than the performance of exist...

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CPE: a parallel library for financial engineering applications

Cited by 3 publications

References 8 publications

Resource management with stateful support for analytic applications

Resource management with stateful support for analytic applications

A high performance pair trading application

Trace-Based Dynamic Binary Parallelization

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