Automatic Heterogeneous Runtime Using Signal Processing Domain-Specific and Parallel Patterns
Parallel and signal processing patterns for large-scale radio data applications have been captured with a new domain-specific language (DSL), OptiSDR. The intermediate representations (IR) of the code are optimized at the frontend with the Delite compiler targeted for heterogeneous computing archite...
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| Vydáno v: | International journal of parallel programming Ročník 53; číslo 2; s. 8 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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01.04.2025
Springer Nature B.V |
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| ISSN: | 0885-7458, 1573-7640 |
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| Abstract | Parallel and signal processing patterns for large-scale radio data applications have been captured with a new domain-specific language (DSL), OptiSDR. The intermediate representations (IR) of the code are optimized at the frontend with the Delite compiler targeted for heterogeneous computing architecture (HCA). The design flow begins at the abstract programming model and, at a later stage, addresses tuning of the domain applications to the target HCA comprising GPUs and MCPU, as well as scheduling and optimal memory access. For a variety of signal processing use cases, the framework has shown up to two orders of magnitude higher computational speed than MPI and C++ and comparable performance to architecture-specific CUDA. Additional gains are ease of use, scalable computing, and efficient runtime. |
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| AbstractList | Parallel and signal processing patterns for large-scale radio data applications have been captured with a new domain-specific language (DSL), OptiSDR. The intermediate representations (IR) of the code are optimized at the frontend with the Delite compiler targeted for heterogeneous computing architecture (HCA). The design flow begins at the abstract programming model and, at a later stage, addresses tuning of the domain applications to the target HCA comprising GPUs and MCPU, as well as scheduling and optimal memory access. For a variety of signal processing use cases, the framework has shown up to two orders of magnitude higher computational speed than MPI and C++ and comparable performance to architecture-specific CUDA. Additional gains are ease of use, scalable computing, and efficient runtime. |
| ArticleNumber | 8 |
| Author | Zaidi, Yaseen Winberg, Simon |
| Author_xml | – sequence: 1 givenname: Yaseen surname: Zaidi fullname: Zaidi, Yaseen email: yaseen.zaidi@cranfield.ac.uk organization: Centre for Systems, Simulation and Analytics, Cranfield Defence and Security, Cranfield University, Defence Academy of the United Kingdom – sequence: 2 givenname: Simon surname: Winberg fullname: Winberg, Simon organization: Radar Remote Sensing Group, University of Cape Town |
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| SubjectTerms | Computation Computer architecture Computer Science Data compression Domain specific languages Language Linear algebra Optimization Processor Architectures Remote sensing Run time (computers) Semantics Signal processing Software Software Engineering/Programming and Operating Systems Theory of Computation |
| Title | Automatic Heterogeneous Runtime Using Signal Processing Domain-Specific and Parallel Patterns |
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