scholarly journals Measuring the dynamic energy efficiency of FPGAs over processors

2021 ◽  
Author(s):  
Muhammad Umair Zafar

This work investigates the dynamic energy efficiency of the parallel execution model of an FPGA and the sequential execution model of a processor, for latency-insensitive applications. We create the temporal implementations (sequential instructions) of the MCNC benchmarks to be executed on a processor that employs a 4LUT as its functional unit. This processor is ~716 times inefficient for dynamic energy than a 4LUT FPGA, mainly due to the large amount of memory (instruction/data) that is required to encode the 4LUT based instructions. The size of the memory (instruction/data) can be reduced by increasing the data-path width and the logic complexity of the ASIC-based functional units of the processor. Particularly, at 64-bit data-path width and when the (instruction/data) memory sizes are reduced to less than ~9% of their corresponding 4LUT-based instructions, the processor with ASIC-based complex functional unit can achieve higher dynamic energy efficiency than the FPGA for MCNC benchmarks.

2021 ◽  
Author(s):  
Muhammad Umair Zafar

This work investigates the dynamic energy efficiency of the parallel execution model of an FPGA and the sequential execution model of a processor, for latency-insensitive applications. We create the temporal implementations (sequential instructions) of the MCNC benchmarks to be executed on a processor that employs a 4LUT as its functional unit. This processor is ~716 times inefficient for dynamic energy than a 4LUT FPGA, mainly due to the large amount of memory (instruction/data) that is required to encode the 4LUT based instructions. The size of the memory (instruction/data) can be reduced by increasing the data-path width and the logic complexity of the ASIC-based functional units of the processor. Particularly, at 64-bit data-path width and when the (instruction/data) memory sizes are reduced to less than ~9% of their corresponding 4LUT-based instructions, the processor with ASIC-based complex functional unit can achieve higher dynamic energy efficiency than the FPGA for MCNC benchmarks.


1983 ◽  
Vol 11 (3) ◽  
pp. 349-355 ◽  
Author(s):  
Shinji Umeyama ◽  
Koichiro Tamura

Author(s):  
Mohammad Saber Golanbari ◽  
Anteneh Gebregiorgis ◽  
Elyas Moradi ◽  
Saman Kiamehr ◽  
Mehdi B. Tahoori

2005 ◽  
Vol 15 (3) ◽  
pp. 353-401 ◽  
Author(s):  
CLEMENS GRELCK

Classical application domains of parallel computing are dominated by processing large arrays of numerical data. Whereas most functional languages focus on lists and trees rather than on arrays, SAC is tailor-made in design and in implementation for efficient high-level array processing. Advanced compiler optimizations yield performance levels that are often competitive with low-level imperative implementations. Based on SAC, we develop compilation techniques and runtime system support for the compiler-directed parallel execution of high-level functional array processing code on shared memory architectures. Competitive sequential performance gives us the opportunity to exploit the conceptual advantages of the functional paradigm for achieving real performance gains with respect to existing imperative implementations, not only in comparison with uniprocessor runtimes. While the design of SAC facilitates parallelization, the particular challenge of high sequential performance is that realization of satisfying speedups through parallelization becomes substantially more difficult. We present an initial compilation scheme and multi-threaded execution model, which we step-wise refine to reduce organizational overhead and to improve parallel performance. We close with a detailed analysis of the impact of certain design decisions on runtime performance, based on a series of experiments.


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