Best Short Paper at FCCM 2017 gets 30x from Python-based PYNQ development versus C-based, hand-coded designs for Zynq SoC

2017年5月17日 | By News | Filed in: News.

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A paper titled “Evaluating Rapid Application Development with Python for Heterogeneous Processor-based FPGAs” that discusses the advantages and efficiencies of Python-based development using the PYNQ development environment—based on the Python programming language and Jupyter Notebooks—and the Digilent PYNQ-Z1 board, which is based on the Xilinx Zynq SoC, recently won the Best Short Paper award at the 25th IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 2017) held in Napa, CA. The paper’s authors—Senior Computer Scientist Andrew G. Schmidt, Computer Scientist Gabriel Weisz, and Research Director Matthew French from the USC Viterbi School of Engineering’s Information Sciences Institute—evaluated the impact of, the performance implications, and the bottlenecks associated with using PYNQ for application development on Xilinx Zynq devices. The authors then compared their Python-based results against existing C-based and hand-coded implementations.

 

 

The authors do a really nice job of describing what PYNQ is:

 

 

“The PYNQ application development framework is an open source effort designed to allow application developers to achieve a “fast start” in FPGA application development through use of the Python language and standard “overlay” bitstreams that are used to interact with the chip’s I/O devices. The PYNQ environment comes with a standard overlay that supports HDMI and Audio inputs and outputs, as well as two 12-pin PMOD connectors and an Arduino-compatible connector that can interact with Arduino shields. The default overlay instantiates several MicroBlaze processor cores to drive the various I/O interfaces. Existing overlays also provide image filtering functionality and a soft-logic GPU for experimenting with SIMT [single instruction, multiple threads] -style programming. PYNQ also offers an API and extends common Python libraries and packages to include support for Bitstream programming, directly access the programmable fabric through Memory-Mapped I/O (MMIO) and Direct Memory Access (DMA) transactions without requiring the creation of device drivers and kernel modules.”

 

 

They also do a nice job of explaining what PYNQ is not:

 

 

“PYNQ does not currently provide or perform any high-level synthesis or porting of Python applications directly into the FPGA fabric. As a result, a developer still must use create a design using the FPGA fabric. While PYNQ does provide an Overlay framework to support interfacing with the board’s IO, any custom logic must be created and integrated by the developer. A developer can still use high-level synthesis tools or the aforementioned Python-to-HDL projects to accomplish this task, but ultimately the developer must create a bitstream based on the design they wish to integrate with the Python [code].”

 

 

Consequently, the authors did not simply rely on the existing PYNQ APIs and overlays. They also developed application-specific kernels for their research based on the Redsharc project (see “Redsharc: A Programming Model and On-Chip Network for Multi-Core Systems on a Programmable Chip”) and they describe these extensions in the FCCM 2017 paper as well.

 

 

 

Redsharc Project.jpg

 

 

 

So what’s the bottom line? The authors conclude:

 

“The combining of both Python software and FPGA’s performance potential is a significant step in reaching a broader community of developers, akin to Raspberry Pi and Ardiuno. This work studied the performance of common image processing pipelines in C/C++, Python, and custom hardware accelerators to better understand the performance and capabilities of a Python + FPGA development environment. The results are highly promising, with the ability to match and exceed performances from C implementations, up to 30x speedup. Moreover, the results show that while Python has highly efficient libraries available, such as OpenCV, FPGAs can still offer performance gains to software developers.”

 

In other words, there’s a vast and unexplored territory—a new, more efficient development space—opened to a much broader system-development audience by the introduction of the PYNQ development environment.

 

For more information about the PYNQ-Z1 board and PYNQ development environment, see:

 

 

 

 

 

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May 16, 2017 at 08:25PM


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