A Scalable FPGA Design for Cloud N-Body Simulation

Sozzo, Emanuele Del; Rabozzi, Marco; Tucci, Lorenzo; Sciuto, D.; Santambrogio, Marco D.

doi:10.1109/asap.2018.8445106

Cited by 12 publications

(13 citation statements)

References 15 publications

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“…CAOS, after profiling and analyzing the application in the frontend, properly identified the force computation as the target function to accelerate and matched it to the Master/Slave architectural template. As we can see from Table 8.1, the CAOS implementation targeting an Amazon F1 instance greatly outperforms, both in terms of performance and energy efficiency, the software implementation from [5] running in parallel on 40 threads on an Intel Xeon E5-2680 v2 and the implementation from [4] on a Xilinx VC707 board. Nevertheless, the bespoke implementation from [5] targeting the same hardware provides 11% higher performance than the CAOS one.…”

Section: Resultsmentioning

confidence: 98%

“…As we can see from Table 8.1, the CAOS implementation targeting an Amazon F1 instance greatly outperforms, both in terms of performance and energy efficiency, the software implementation from [5] running in parallel on 40 threads on an Intel Xeon E5-2680 v2 and the implementation from [4] on a Xilinx VC707 board. Nevertheless, the bespoke implementation from [5] targeting the same hardware provides 11% higher performance than the CAOS one. However, the CAOS design was achieved semi-automatically in approximately a day of work, while the design from [5] required several weeks of manual effort.…”

Section: Resultsmentioning

confidence: 98%

“…Nevertheless, the bespoke implementation from [5] targeting the same hardware provides 11% higher performance than the CAOS one. However, the CAOS design was achieved semi-automatically in approximately a day of work, while the design from [5] required several weeks of manual effort.…”

Section: Resultsmentioning

confidence: 99%

“…Performance and energy efficiency of the all-pairs N-Body algorithm accelerated via CAOS and the results achieved by bespoke designs proposed in[4,5] Results achieved by CAOS on the Curran approximation algorithm with 30 and 780 averaging points compared against CPU and the bespoke FPGA-based implementations from[15] …”

mentioning

confidence: 99%

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CAOS: CAD as an Adaptive Open-Platform Service for High Performance Reconfigurable Systems

Rabozzi

2019

Special Topics in Information Technology

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The increasing demand for computing power in fields such as genomics, image processing and machine learning is pushing towards hardware specialization and heterogeneous systems in order to keep up with the required performance level at sustainable power consumption. Among the available solutions, Field Programmable Gate Arrays (FPGAs), thanks to their advancements, currently represent a very promising candidate, offering a compelling trade-off between efficiency and flexibility. Despite the potential benefits of reconfigurable hardware, one of the main limiting factor to the widespread adoption of FPGAs is complexity in programmability, as well as the effort required to port software solutions to efficient hardware-software implementations. In this chapter, we present CAD as an Adaptive Open-platform Service (CAOS), a platform to guide the application developer in the implementation of efficient hardware-software solutions for high performance reconfigurable systems. The platform assists the designer from the high-level analysis of the code, towards the optimization and implementation of the functionalities to be accelerated on the reconfigurable nodes. Finally, CAOS is designed to facilitate the integration of external contributions and to foster research on Computer Aided Design (CAD) tools for accelerating software applications on FPGA-based systems.

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Section: Resultsmentioning

confidence: 98%

Section: Resultsmentioning

confidence: 98%

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

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CAOS: CAD as an Adaptive Open-Platform Service for High Performance Reconfigurable Systems

Rabozzi

2019

Special Topics in Information Technology

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“…We illustrate the usage of our CAD tool optimizing the N-body physics simulation algorithm. We demonstrate how, starting from a open-source software code [16], the user quickly obtains a design having performance comparable to a state-of-the-art bespoke implementation [15]. In this example, we target the Xilinx Virtex UltraScale+ VU9P board on Amazon Web Service (AWS) with a design frequency set to 125MHz.…”

Section: N-body Simulation Test Casementioning

confidence: 99%