虽然Guass 11 还未被破解，Gauss 12 的时代已经悄悄来临了。
http://www.aptech.com/

个人看法：
Gauss 之所以不像Matlab 般如此受欢迎，其原因应该是还没被普及化。
要普京化，就应该鼓励学生去应用它。往往应用者放弃使用Gauss 的其中原因就是找不到破解。
不像Matlab，虽然每年都有2个版本，可是每次网上都能找到相对应的破解，对Guass而言，就是伤不起呀。

New Graphics in GAUSS 12

• Interactive graphics:
  
  • Hide and restore curves with the click of a button.
  • Improved zoom and panning.
  • Rotate 3-D graphics.
    
• Full color palate with 140 named colors or use any RGB value.
• Export to JPEG, PDF, PNG, SVG, TIFF and more.
• Easier to use.
• Change settings programatically or with easy window based options.
  

More Powerful Debugger in GAUSS 12New local variable and watch windows.

• Organized list of in-scope and user-specified watch variables.
• Displays variable name, dimensions, type and first value.
• Automatically and instantly updated with every step.
• One click to view full contents of any matrix.
  

New call stack window.

• Displays the chain of procedure calls, including procedure name, file name and the line of each call.
• One click to view the file and line of any stack frame in the list. This click will also update the local variable window to show the variables local to that stack frame location.
  

User interface enhancements in GAUSS 12Program Input Output Window

• Combined program input/output window available on every page in the user interface.
• Shows live output when switching between pages.
• Search through your program output with CTRL+F.
• Prints output faster than GAUSS 11 with no need need to add print /flush statements for live screen updates.
  

New Source Formatter

• Correctly formats an entire source file or highlighted text with one hot-key or from a context menu.
  

Command History Window

• Organized by session or date.
• Select a group of commands and send them to a new file.
• Subtle "tiger striped" for enhanced readability.
  

Error Window

• Easier to manage - can be set to apear only upon the occurence of an error and disapear when the next command is run, or the user may keep it open always if desired.
  

Notifications

• Unobtrusive window notifications display at the bottom right of your screen for 5 seconds.
• Can be set to notify you of errors, the end of a job, when your GAUSS program is waiting for input, or turned off completely.
  

New Random Number Suite in GAUSS 12Choice of six high quality underlying random number generators, including Mersenne-Twister 19937, Mersenne-Twister 2203 and the MRG32k3a.More than 15 distributions available, including multivariate normal.Parallel random number generation.Option for simpler syntax.No need to change existing code.Parallel Random Number Generation:GAUSS 12 offers two methods for parallel random number generation, through the use of multiple streams or with block-skipping.Multiple StreamsMost random number generators will produce a sequence of random numbers that is equal to their period length. However some random number generators, such as the Mersenne-Twister 2203 include in GAUSS 12, can create more than one substream of random numbers equal in length to their full period.To take advantage of this feature, you need to create a state from the desired substream with the function rndCreateState and pass it in to the random number generating function of your choice.// Create a state from the 103rd and 219th substream
// of the Mersenne-Twister 2203 RNG
seed = 83934003;
state1 = rndCreateState( "mt2203-103", seed );
state2 = rndCreateState( "mt2203-219", seed );

// Create a 5x5 random normal matrix with each of these
// respective state vectors.
{ x, state1 } = rndn( 5, 5, state1 );
{ y, state2 } = rndn( 5, 5, state2 );

The random numbers from these newly created state vectors will allow the creation of independent streams of random numbers that may be safely passed into multithreaded code.Block SkippingBlock skipping allows you to advance a random number stream a specified number of values without calculating them. As a simple example, we will create a random number state vector and then skip it forward by two numbers.// Create a state using the MRG32k3a generator
seed = 6354123452;
state = rndCreateState( "mrg32k3a", seed );

// Create a new state that will skip ahead two numbers
statePlusTwo = rndStateSkip( 2, state );
{ r, state } = rndn( 4, 1, state );
{ r2, statePlusTwo } = rndn( 2, 1, statePlusTwo );
print r;
1.1957677
0.14053340
-0.16571487
0.22579434
print r2;
-0.16571487
0.22579434
Option for simple syntax and no need for code changeWhile the options for creating parallel, threadsafe random number calls are available, you are not required to pass in a state vector, or to change your code in any way. The new random number functions all allow you to pass in and return the state vector as an optional argument. For more complex programs you may use any of the methods from above. However, for simpler programs or initial prototyping you are not required to use or create a state vector.r = rndn( rows, cols );
In these cases, simple syntax as shown above can be used for any of the new random number functions.
New and improved functions in GAUSS 12Speed Improvements

• Financial Functions
  
  • AmericanBinomCall, AmericanBinomCall_Greeks, AmericanBinomCall_ImpVol, AmericanBinomPut, AmericanBinomPut_Greeks, AmericanBinomPut_ImpVol, AmericanBSCall, AmericanBSCall_Greeks, AmericanBSCall_ImpVol, AmericanBSPut, AmericanBSPut_Greeks, AmericanBSPut_ImpVol, EuropeanBinomCall, EuropeanBinomCall_Greeks, EuropeanBinomCall_ImpVol, EuropeanBinomPut, EuropeanBinomPut_Greeks, EuropeanBinomPut_ImpVol, EuropeanBSCall, EuropeanBSCall_Greeks, EuropeanBSCall_ImpVol, EuropeanBSPut, EuropeanBSPut_Greeks, EuropeanBSPut_ImpVol
    
• Linear Algebra
  
  • X'*Y: for small and medium sized matrices.
  • Matrix tranpose for large matrices; approximately 400 x 400 or larger.
  • Takes advantage of new Intel AVX instructions:
    
    • Matrix multiply: In-house testing shows approximately 20% faster for 30 x 30 matrix, nearly 40% faster for 150 x 150 matrix, and twice as fast for 10,000 x 10,000 matrix on a compatible machine.
    • Linear Solve: In-house testing shows approximately 12% faster for 200 x 200 matrix, nearly 25% faster for 500 x 500 matrix, 40% faster for 2,000 x 2,000 matrix.
    • Matrix inversion: approximately 20% faster for a 500 x 500 matrix, nearly 40% faster for 1,000 x 1,000 matrix.
      
• Distribution Functions
  
  • cdfBeta
  • cdfBinomialInv
  • cdfGenPareto
  • cdfLaplace, cdfLaplaceInv
  • cdfNegBinomialInv
  • cdfPoissonInv
    

New Functionality

• New random number distributions
  
  • Cauchy
  • Exponential
  • Geometric
  • Gumbel
  • Laplace
  • Log-normal
  • Multivariate normal
  • Weibull