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Floating point benchmark suite for multi-core processors

Posted: 08 Aug 2013 ?? ?Print Version ?Bookmark and Share

Keywords:EEMBC? benchmark suite? embedded? processors?

The Embedded Microprocessor Benchmark Consortium(EEMBC) recently debuted FPMark, a new benchmark suite that tracks the performance of embedded processors with floating-point hardware units (FPU), an increasingly popular and necessary feature to support graphics, audio, motor control, and many other high-end processing tasks.

The FPMark benchmark suite contains single (32bit) and double (64bit) precision workloads, as well as a mixture of small to large data sets to support microcontrollers to high-end processors, respectively. The suite allows users to evaluate FPU performance on the basis of consistent and controlled data, delivering honest, reliable, and unbiased metrics to serve the needs of processor vendors, compiler vendors, and system developers.

Using floating-point (FP) representation enables more accurate calculations of fractional values than fixed-point numbers (integers) because exponents allow the decimal point to shift. Moreover, floating- point math makes numerical computation much easier and many algorithms implemented with floating point take fewer cycles to execute than fixed-point code (assuming similar precision). To take advantage of this efficiency, many embedded processors include hardware floating-point units (FPUs) to support these higher levels of precision.

The EEMBC FPMark Suite uses 10 diverse kernels to generate 53 workloads, each of which self-verify to ensure correct execution of the benchmark. These workloads are built on the same infrastructure as EEMBC MultiBench, allowing the user to launch multiple contexts and demonstrate multi-core scalability, as well as greatly simplifying the effort required to port the benchmarks to bare metal or implementations running Linux. The kernels in FPMark include a mixture of general-purpose algorithms (such as Fast Fourier Transform, linear algebra, ArcTan, Fourier coefficients, Horner's method, and Black Scholes) and complex algorithms (such as a neural network routine, a ray tracer, and an enhanced version of Livermore Loops).

"Until now, the industry has lacked a reliable, useful, and consistent floating-point benchmark. In the same way that EEMBC CoreMark was intended to be a "better Dhrystone," FPMark provides an extreme improvement over the easily manipulated Whetstone and Linpack," said EEMBC president, Markus Levy. "The FPMark will expose and highlight the performance gains from innovations in FPU development in terms of real application performance."

"Developing a reliable floating-point benchmark is a complex challenge C one that EEMBC overcame using many years of benchmark development experience. While many people have attempted to create a floating-point benchmark, most do not comprehend the extra effort required to ensure that the workload executes comparably regardless of compiler or hardware used," said Linley Gwennap, president and principal analyst of The Linley Group. "For example, it's important that the FPMark was constructed in such a way to support advanced compiler optimisations, but not at the expense of optimising away work that must be done during the execution of the benchmark."

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