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DSP Builder for FPGAs: Getting the merit it deserves

14 Sep 2015  | Michael Parker

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For FPGAs to act as accelerators to high performance CPUs, vector support is fundamental to for highly parallel algorithms, with a focus on linear algebra.

Math.h library

Along with native floating-point support comes the need for math functions. DSP Builder provides a full complement of math functions using underlying algorithms that are specifically designed for efficient FPGA implementation.

FPGA design

Due to the high Fmax and low logic usage of the math library, designers no longer need to craft their implementations to minimise use of functions such as divide, square root, trigonometric, logarithm and exponent operators.

System simulation in Mathworks' environment

Complex algorithms must be developed and verified at the system level. Model-based designs allow the system engineer to leverage the extensive capabilities and toolboxes of Mathworks products. Oftentimes, the test bench can be more complex than the algorithm being implemented, so the ability to simulate using MATLAB and Simulink is extremely useful.

Simulink simulation

Bit- and cycle-accurate Simulink simulation, automatic verification in RTL simulation and 'System In The Loop' verification on connected hardware

The DSP Builder design can also be simulated within the Mathworks environment, thereby allowing full visibility and easy debug before any hardware is involved. DSP Builder will also provide resource estimations (e.g., logic, DSP blocks, memory) without the need to perform any FPGA compiles, which can be fairly time-consuming. This allows for rapid design space exploration, enabling the designer to make trade-offs and ensure the design will fit into the chosen FPGA prior to invoking synthesis, fitting, and routing. Furthermore, DSP Builder will generate a ModelSim testbench using the same vectors generated by Mathworks testbench, and also run the hardware verification. This certifies the fidelity of the DSP Builder code-generation process, ensuring the behaviour observed in the original Mathworks simulation is faithfully reproduced in hardware.

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