Version 9_0_2 is released on windows, linux-glibc2.3, linux-glib2.2, linux-glib2.1, and Solaris 32 bits.

NEW: Automatic sizing of operands in DSP applications:

FinSim 9_0_2 provides running examples of using FinMath in order to determine the size of operands in DSP applications

without leaving your Verilog simulator.

FinMath is a super set of the Verilog IEEE 1364 language having, as described in chapter 8 of FinSim's User's Guide

available at www.fintronic.com (click on Support, FAQ, download FinSim's Users Guide), the following features:

a) additional system functions, such as $VpSin, $VpCos, $VpTan, $VpCtan, $VpAsin, $VpAcos, $VpAtan, $VpActan,

$VpPow, $VpPow2, $VpLog, $VpLn, $VpAbs, $VpFloor, $VpHypot, etc.

b) the capability of declaring variable precision objects by using the attributes varprec = data and

varprec = descriptor using the standard Verilog syntax.

Such objects can store values in fixed and floating point formats and the size of the formats can be changed

during the execution of the simulation, by using $VpAssociateDescriptorToData and $VpSetDescriptorInfo.

c) the capability of overloading arithmetic and logical operators as well as assignment operators, i.e. the

compiler will find, if possible, the appropriate functions to implement the described functionality, without

needing conversion functions.

d) support for displaying variable precision objects (using the formats %y, %k, %h).

The misc/demo_vp directory of the FinSim distribution contains three running examples of DSP design using FinMath

Each of the examples is fully contained in each of the three files: filter_real.v, filter_vp.v, filter_vp_fix.v.

The example in filter_real.v shows

i) loading of input samples and of ideal output samples into arrays of reals. Note the ease with which one can

create the intended waveform using FinMath.

ii) a filtering of the input samples according to a Butterworth IIR LP order 5 filter. The high frequency signals

are eliminated.

iii) a comparison between the ideal output samples and the samples of the filtered output done both via display and via

the task compute distance.

iv) an example of plotting the input and filtered output using ptplot from UC Berkeley.

v) fft applied to both the input and the filtered output, in order to check the correctness of the filtering.

Note that three 1024 * 1024 point Fast Fourier transforms are performed in less than one minute on a 2GHz

Pentium if the operands are of type real as in the filter_real.v example.

The examples in filter_vp.v and filter_vp_fix.v differ only in that the first one has operands in variable

precision floating point and the second one has operands in variable precision fixed point representation.

Each of these descriptions use the FinMath language which is a super set of Verilog in order to determine the

optimal size of the operands by doing the following:

i) loading of input samples and of ideal output samples

ii) a filtering of the input samples according to a Butterworth IIR LP order 5 filter.

iii) a comparison between the ideal output samples and the samples of the filtered output done via the task

compute distance. While the distance between the filtered output and the ideal output is larger than the

acceptable distance the number of bits of the fractional part of the representation of the operands is

increased and steps i) through iii) are performed again.

9.0.2 Release date: 3/7/2007

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