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Website: http://www.catalyticinc.com/

Catalytic is focused on producing software products that greatly increase the productivity of DSP programmers, thereby greatly reducing the time it takes to get a DSP algorithm from onto a target DSP processor. Catalytic's products focus on the difficult bottlenecks of DSP programming: converting floating-point algorithms into fixed-point implementations, providing high-speed simulation, and...More»

Address: 1076A East Meadow Circle Palo Alto, CA 94303 Map it »

Phone: 650-846-2555

Email: support@agilityds.com

Founded: 2001

Industry: Software

Sub-Industry: Business Application

Legal Structure: Corporation

Ownership: Private

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Date	Type	Capital Amount	Post-Money Valuation	Investors
05/12/2006	Series B	7M	Unknown	CMEA Ventures, ITU Ventures, NEA

Name:	Agility RMS
Product URL:	http://agilityds.com/products/matlab_based_products/rms/default.aspx
Description:	The increasing complexity of signal processing algorithms drives the need for faster simulation for validation. Agility RMS accelerates algorithms written in M-code. The accelerated simulation speed approaches the simulation speed of hand-coded C but is automatically generated from the source MATLAB®. Agility RMS automatically converts user's MATLAB into a compiled MEX-file, delivering compiled code performance seamlessly within the MATLAB environment. Agility RMS (Rapid MATLAB Simulator) features fast simulation of MATLAB code and fixed-point analysis tools for quantization and datapath optimization. Blazing Fast Simulation RMS AccelerationAgility RMS converts M-code functions into a compiled library that uses the MATLAB standard MEX interface. This library produces results identical to the original algorithm, but executes much faster. Agility RMS is integrated seamlessly within MATLAB. Agility RMS uses proprietary, state-of-the-art compilation technology, including interprocedural analysis and optimizations, type inferencing and advanced loop and dependency analysis. The result: faster execution of MATLAB algorithms. Algorithm Acceleration tableBecause MATLAB does use compiled code for some critical functions, like FFT, the performance gain RMS will provide varies. The graph to the right gives some guidelines for levels of acceleration for different styles of MATLAB code. In addition, a table of example acceleration factors for some common signal processing applications is shown. Easy to Use Agility RMS is designed to be used with existing MATLAB code. Based on an execution profile of a program, it will automatically convert candidate functions into a MEX-file. RMS will also recommend code modifications for additional acceleration. Agility MCS supports a large subset of the MATLAB language, including many of the commonly used features for modeling signal processing systems: * Operators: arithmetic, matrix, logical, and bitwise operators * Data types: real/complex, logical, structures * Shapes: scalars, vectors, matrices, n-dimensional arrays * Persistent and global variables * Flow control constructs: if-then-else, for loops, while loops, switch * Common mathematical functions (e.g. sqrt, sin, atan) * Numerous built-in functions * Many plotting functions * Most of the Signal Processing and Communications toolboxes and Image Processing toolbox. Additional Benefits for Fixed-Point Designers Without Agility fast simulation technology, simulation of fixed-point algorithms can be unacceptably slow. As a result, developers usually do not quantize their design until they have migrated out of the MATLAB environment. In addition to blazing fast simulation, Agility RMS also includes analysis tools to dramatically ease the quantization process. These fixed-point analysis tools: * Display the types of all variables in a MATLAB design * Recommend quantization based on simulation runs Flag overflows and other potential quantization errors With Agility RMS, developers can now quantize MATLAB designs and run full system simulations inside the MATLAB environment. Developers can continue to use the MATLAB development environment to develop, optimize, and verify their MATLAB algorithms.
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