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MVPA: An FPGA based multi-vector processor architecture
- Source :
- 2016 13th International Bhurban Conference on Applied Sciences and Technology (IBCAST).
- Publication Year :
- 2016
- Publisher :
- IEEE, 2016.
-
Abstract
- With the increase in FPGA density and performance, the demand for multiple high-performance computing (HPC) units has been increased for various scientific and technological fields. Multi-scalar processor architectures do not give the best performance on FPGAs for HPC applications. This performance degradation demands a parameterizable high-performance processor architecture to process HPC applications. In this article, we proposed an FPGA based Multi-Vector Processor Architecture by integrating an efficient scheduler into existing Programmable Vector Memory Controller (PVMC). The proposed design is known as Multi-Vector Processor Architecture (MVPA) which proficiently handles multiple vectorized tasks and their data movements. The system is tested on n Altera FPGA DE4 development board. The MVPA system results are compared with a generic Multi-Vector Processor and multi-scalar core systems. The results show that the MVPA system handles computation task more efficiently and improves system performance between 8.1x to 30.1x and 1.99x to 4.31x against scalar multi-core and generic Multi-Vector Processor systems respectively for 10 applications.
- Subjects :
- Computer science
Application-specific instruction-set processor
Process (computing)
020206 networking & telecommunications
02 engineering and technology
Memory controller
Microarchitecture
Vector processor
Task (computing)
Computer architecture
Media processor
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Field-programmable gate array
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2016 13th International Bhurban Conference on Applied Sciences and Technology (IBCAST)
- Accession number :
- edsair.doi...........a23e0416e482528dc15bb0ca52af9b16
- Full Text :
- https://doi.org/10.1109/ibcast.2016.7429879