Manycore processors can replace FPGAs
Latency and scalability are among the criteria to consider when weighing FPGA versus manycore processor use
Peter argues that GPGPU technology can, in many instances, replace either/or FPGAs and DSPs for reasons including greater performance, easier programming and lower cost.
A single binary can be run on different devices with different core counts. In many cases this can provide migration to new platforms with minimal pain.
Similarly, SMP applications for TILE processors can be written to automatically scale to a larger number of cores when newer devices become available.
In contrast, moving an FPGA application to a newer device can mean substantially reworking the hardware expression code to fit a different target platform even if the algorithm remains the same.
Commercial-grade GPGPU boards (Figure 3) can be bought for as little as $50 and as much as $4,000 for the latest boards targeted at supercomputing applications. A board containing a high-end Virtex-6 FPGA will likely run in the region of $4,000. Tilera boards will most likely be much higher than both of these due to their niche nature. Ruggedized versions of all three types will be much higher due to lower volumes, board construction techniques, testing and screening. For example, a fully ruggedized, conduction-cooled GPU board can cost in the region of $7,000. Such boards are required for military/aerospace applications as commercial boards will not survive the environmental stresses of deployment in harsh environments and do not have the required life cycle support for long-term programs.
For many use cases FPGA performance with regard to processing prowess and tight latency remains unrivalled. However, there are many other cases where the use of a multicore device can and should be considered. Due to their fixed point performance, TILE processors can be considered as a direct replacement for FPGAs. As GPGPUs are more adept at floating point operation, they can be considered as both a replacement of, and a complement to, FPGAs.
Multicore processors are making their way ever closer to the sensor, and it’s likely that modules will come to market soon – with such devices sitting right behind an analog-to-digital converter (ADC) where the FPGA used to be. Some applications that moved from General Purpose Processors (GPPs) such as PowerPC with AltiVec to arrays of FPGAs are now starting to migrate to manycore architectures. For example, medical imaging devices such as Computed Tomography backprojection and Magnetic Resonance Imaging are now employing GPGPUs to generate their images.
Radar systems that currently employ heterogeneous mixes of FPGAs and GPPs are evaluating the viability of using GPGPUs to reduce the Size, Weight and Power (SWaP) of the processing subsystems to allow deployment in smaller platforms such as UAVs or increase processing capability in the same footprint. Some imaging applications such as 360-degree situational awareness that once used dedicated hardware now use TILE processors and GPUs to ingest multiple camera streams, then to warp, stitch, and display panoramas (Figure 4).
Given the ease of programming these manycore devices, their processing power, and their low acquisition cost and typically lower associated development cost, much to commends them for applications once dominated by programmable hardware arrays.
Peter Thompson graduated in 1980 from the University of Birmingham, UK, with a BSc Eng. (Hons) in Electrical and Electronic Engineering. He began his career at Racal Redac, eventually joining Radstone Technology. He is currently Director of Applications, Business Development, at GE Intelligent Platforms, tasked with evangelizing new technologies to customers and gathering market intelligence on new technology directions.