High throughput spatial convolution filters on FPGAs

Digital signal processing (DSP) on field- programmable gate arrays (FPGAs) has long been appealing because of the inherent parallelism in these computations that can be easily exploited to accelerate such algorithms. FPGAs have evolved significantly to further enhance the mapping of these algorithms, included additional hard blocks, such as the DSP blocks found in modern FPGAs. Although these DSP blocks can offer more efficient mapping of DSP computations, they are primarily designed for 1-D filter structures. We present a study on spatial convolutional filter implementations on FPGAs, optimizing around the structure of the DSP blocks to offer high throughput while maintaining the coefficient flexibility that other published architectures usually sacrifice. We show that it is possible to implement large filters for large 4K resolution image frames at frame rates of 30–60 FPS, while maintaining functional flexibility

Square-rich fixed point polynomial evaluation on FPGAs

Polynomial evaluation is important across a wide range of application domains, so significant work has been done on accelerating its computation. The conventional algorithm, referred to as Horner's rule, involves the least number of steps but can lead to increased latency due to serial computation. Parallel evaluation algorithms such as Estrin's method have shorter latency than Horner's rule, but achieve this at the expense of large hardware overhead. This paper presents an efficient polynomial evaluation algorithm, which reforms the evaluation process to include an increased number of squaring steps. By using a squarer design that is more efficient than general multiplication, this can result in polynomial evaluation with a 57.9% latency reduction over Horner's rule and 14.6% over Estrin's method, while consuming less area than Horner's rule, when implemented on a Xilinx Virtex 6 FPGA. When applied in fixed point function evaluation, where precision requirements limit the rounding of operands, it still achieves a 52.4% performance gain compared to Horner's rule with only a 4% area overhead in evaluating 5th degree polynomials

Parametric, Secure and Compact Implementation of RSA on FPGA

We present a fast, efficient, and parameterized modular multiplier and a secure exponentiation circuit especially intended for FPGAs on the low end of the price range. The design utilizes dedicated block multipliers as the main functional unit and Block-RAM as storage unit for the operands. The adopted design methodology allows adjusting the number of multipliers, the radix used in the multipliers, and number of words to meet the system requirements such as available resources, precision and timing constraints. The architecture, based on the Montgomery modular multiplication algorithm, utilizes a pipelining technique that allows concurrent operation of hardwired multipliers. Our design completes 1020-bit and 2040-bit modular multiplications in 7.62 μs and 27.0 μs, respectively. The multiplier uses a moderate amount of system resources while achieving the best area-time product in literature. 2040-bit modular exponentiation engine can easily fit into Xilinx Spartan-3E 500; moreover the exponentiation circuit withstands known side channel attacks

A general framework for efficient FPGA implementation of matrix product

Original article can be found at: http://www.medjcn.com/ Copyright Softmotor LimitedHigh performance systems are required by the developers for fast processing of computationally intensive applications. Reconfigurable hardware devices in the form of Filed-Programmable Gate Arrays (FPGAs) have been proposed as viable system building blocks in the construction of high performance systems at an economical price. Given the importance and the use of matrix algorithms in scientific computing applications, they seem ideal candidates to harness and exploit the advantages offered by FPGAs. In this paper, a system for matrix algorithm cores generation is described. The system provides a catalog of efficient user-customizable cores, designed for FPGA implementation, ranging in three different matrix algorithm categories: (i) matrix operations, (ii) matrix transforms and (iii) matrix decomposition. The generated core can be either a general purpose or a specific application core. The methodology used in the design and implementation of two specific image processing application cores is presented. The first core is a fully pipelined matrix multiplier for colour space conversion based on distributed arithmetic principles while the second one is a parallel floating-point matrix multiplier designed for 3D affine transformations.Peer reviewe

Comparison of Scalable Montgomery Modular Multiplication Implementations Embedded in Reconfigurable Hardware

International audienceThis paper presents a comparison of possible approaches for an efficient implementation of Multiple-word radix-2 Montgomery Modular Multiplication (MM) on modern Field Programmable Gate Arrays (FPGAs). The hardware implementation of MM coprocessor is fully scalable what means that it can be reused in order to generate long-precision results independently on the word length of the originally proposed coprocessor. The first of analyzed implementations uses a data path based on traditionally used redundant carry-save adders, the second one exploits, in scalable designs not yet applied, standard carry-propagate adders with fast carry chain logic. As a control unit and a platform for purely software implementation an embedded soft-core processor Altera NIOS is employed. All implementations use large embedded memory blocks available in recent FPGAs. Speed and logic requirements comparisons are performed on the optimized software and combined hardware-software designs in Altera FPGAs. The issues of targeting a design specifically for a FPGA are considered taking into account the underlying architecture imposed by the target FPGA technology. It is shown that the coprocessors based on carry-save adders and carry-propagate adders provide comparable results in constrained FPGA implementations but in case of carry-propagate logic, the solution requires less embedded memory and provides some additional implementation advantages presented in the paper

Series Expansion based Efficient Architectures for Double Precision Floating Point Division

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Automatic rapid prototyping of semi-custom VLSI circuits using FPGAs

Journal ArticleWe describe a technique for translating semi-custom VLSI circuits automatically, integrating two design environments, into field programmable gate arrays (FPGAs) for rapid and inexpensive prototyping. The VLSI circuits are designed using a cell-matrix based environment that produces chips with density comparable to full custom VLSI design. These circuits are translated automatically into FPGAs for testing and system development. A four-bit pipelined array multiplier is used as an example of this translation. The multiplier is implemented in CMOS in both synchronous and asynchronous pipelined versions, and translated into Actel FPGAs both automatically, and by hand for comparison. The six test chips were all found to be fully functional, and the translation efficiency in terms of chip speed and area is shown. This result demonstrates the potential of this approach to system development