| 2 APPLICATION SCENARIOS
| =======================
|
|
| 2.1 Linear, Time-invariant Equalization Model
| =============================================
|
|   1. From the system netlist, the EDA platform determines that a given
|      [Model] is described by an IBIS file.
|
|   2. From the IBIS file, the EDA platform determines that the [Model] is
|      described at least in part by an algorithmic model.
|
|   3. The EDA platform loads the shared library or shared object file
|      containing the algorithmic model, and obtains the addresses of the
|      AMI_Init, AMI_GetWave, and AMI_Close functions.
|
|   4. The EDA platform assembles the arguments for AMI_Init. These
|      arguments include the impulse response of the channel driving the
|      block, a handle for the dynamic memory used by the block, the
|      parameters for configuring the block, and optionally the impulse
|      responses of any crosstalk interferers.
|
|   5. The EDA platform calls AMI_Init with the arguments previously
|      prepared.
|
|   6. AMI_Init parses the configuration parameters, allocates dynamic
|      memory, places the address of the start of the dynamic memory in the
|      memory handle.  Depending on the value of Init_Returns_Filter, it
|      either computes and returns the filter response of the block, or
|      computes the impulse response of the channel modified by the filter
|      response of the block.
|
|   7. The EDA platform completes the rest of the simulation/analysis using
|      the impulse response from AMI_Init as a complete representation of
|      the behavior of the given block combined with the channel, or makes
|      use of the filter response returned by AMI_Init to compute the
|      behavior of the given block combined with the channel.
|
|   8. Before exiting, the EDA platform calls AMI_Close, giving it the
|      address in the memory handle for the block.
|
|   9. AMI_Close de-allocates the dynamic memory for the block and performs
|      whatever other clean-up actions are required.
|
|  10. The EDA platform terminates execution.
|
|
| 2.2 Nonlinear, and / or Time-variant Equalization Model
| =======================================================
|
|   1. From the system netlist, the EDA platform determines that a given
|      block is described by an IBIS file.
|
|   2. From the IBIS file, the EDA platform determines that the block is
|      described at least in part by an algorithmic model.
|
|   3. The EDA platform loads the shared library or shared object file
|      containing the algorithmic model, and obtains the addresses of the
|      AMI_Init, AMI_GetWave, and AMI_Close functions.
|
|   4. The EDA platform assembles the arguments for AMI_Init.  These
|      arguments include the impulse response of the channel driving the
|      block, a handle for the dynamic memory used by the block, the
|      parameters for configuring the block, and optionally the impulse
|      responses of any crosstalk interferers.
|
|   5. The EDA platform calls AMI_Init with the arguments previously
|      prepared.
|
|   6. AMI_Init parses the configuration parameters, allocates dynamic
|      memory and places the address of the start of the dynamic memory in
|      the memory handle.  Depending on the value of Init_Returns_Filter,
|      it either computes and returns the filter response of the block, or
|      computes the impulse response of the channel modified by the filter
|      response of the block.  The EDA platform may make use of the
|      impulse response or the filter response returned by AMI_Init in its
|      further analysis if needed.
|
|   7. The EDA platform generates a time domain input waveform (stimulus)
|      bit pattern.  A long simulation may be broken up into multiple time
|      segments by the EDA platform.  For example, if a million bits are
|      to be simulated, there can be 1000 segments of 1000 bits each, i.e.
|      one time segment comprises 1000 bits.
| 
|   8. For each time segment, the EDA platform calls the transmitter
|      AMI_GetWave function, giving it the input waveform and the address
|      in the dynamic memory handle for the block.
|
|   9. Depending on the value stored in the Use_Init_Output parameters,
|      the EDA platform combines the output of the transmitter AMI_GetWave
|      function with the output(s) of the AMI_Init function(s) with the
|      impulse response of the channel and passes this result to the
|      receiver AMI_GetWave function for each time segment of the
|      simulation.
|
|  10. The output waveform of the receiver GetWave function represents the
|      voltage waveform at the decision point of the receiver.  The EDA
|      platform uses this waveform to complete the simulation/analysis.
|
|  11. Before exiting, the EDA platform calls AMI_Close, giving it the
|      address in the memory handle for the block.
|
|  12. AMI_Close de-allocates the dynamic memory for the block and performs
|      whatever other clean-up actions are required.
|
|  13. The EDA platform terminates execution.
|
|
| 2.3 Reference system analysis flow
| ==================================
|
| System simulations will commonly involve both TX and RX algorithmic
| models, each of which may perform filtering in the AMI_Init call, the
| AMI_Getwave call, or both.  Since both LTI and non-LTI behavior can be
| modeled with algorithmic models, the manner in which models are evaluated
| can affect simulation results.  The following steps are defined as the
| reference simulation flow.  Other methods of calling models and
| processing results may be employed, but the final simulation waveforms
| are expected to match the waveforms produced by the reference simulation
| flow.
|
|
|  Step 1. The simulation platform obtains the impulse response for the
|          analog channel.  This represents the combined impulse response
|          of the transmitter's analog output, the channel and the
|          receiver's analog front end.  This impulse response represents
|          the transmitter's output characteristics without filtering, for
|          example, equalization.
|
|  Step 2. The output of Step 1 is presented to the TX model's AMI_Init
|          call.  If Init_Returns_Filter for the TX model is set to True,
|          the model returns the impulse response of the TX filter.  If it
|          is set to False, the TX AMI_Init call returns the modified
|          impulse response of the channel.  The output of TX AMI_Init is
|          returned to the EDA tool which decides how to make use of it
|          depending on the transmitter’s Init_Returns_Filter and
|          Use_Init_Output parameters.
|
|  Step 3. If the transmitter’s Init_Returns_Filter parameter is set to
|          False, the output of Step 2 is presented to the RX model's
|          AMI_Init call.  If the Init_Returns_Filter is set to True, the
|          EDA tool will combine the output of Step 2 with the output of
|          Step 1 (for example by convolution) before presenting it to the
|          RX model’s AMI_Init call.
|
|  Step 4. The output of Step 3 is presented to the RX model's AMI_Init
|          call.  If Init_Returns_Filter for the RX model is set to True,
|          the model returns the impulse response of the RX filter.  If it
|          is set to False, the RX AMI_Init call returns the filtered
|          response of the channel.  The output of RX AMI_Init is returned
|          to the EDA tool which decides how to make use of it depending
|          on the receiver’s Init_Returns_Filter and Use_Init_Output
|          parameters.
|
|  Step 5. If the receiver’s Init_Returns_Filter parameter is set to
|          False, the output of Step 4 may be presented to the user of the
|          EDA tool, or the EDA tool can further process the results using
|          statistical algorithms.  If the Init_Returns_Filter is set to
|          True, the EDA tool will combine the output of Step 4 with the
|          output of Step 3 (for example by convolution) before presenting
|          it to the user of the EDA tool, or before continuing with the
|          statistical processing of these results.
|
|  Step 6. The simulation platform produces a digital stimulus waveform.  A
|          digital stimulus waveform is 0.5 when the stimulus is “high”,
|          -0.5 when the stimulus is “low”, and may have a value between
|          -0.5 and 0.5 such that transitions occur when the stimulus
|          crosses 0.
|
|  Step 7. The output of step 6 is presented to the TX model's AMI_Getwave
|          call.  If the TX model does not include an AMI_Getwave call,
|          this step is a pass-through step, and the input to step 7 is
|          passed directly to step 8.
|
|  Step 8. The EDA simulation platform combines (for example by
|          convolution) the output of step 7 with the output of several
|          different previous steps depending on the value of the
|          transmitter’s and receiver’s Init_Returns_Filter and
|          Use_Init_Output settings as follows:
|
|          If TX Use_Init_Output = False, combine the outputs of Step 7
|          and Step 1.
|
|          If TX Use_Init_Output = True and TX Retuns_Filter = False,
|          combine the outputs of Step 7 and Step 2.
|
|          If TX Use_Init_Output = True and TX Retuns_Filter = True,
|          combine the outputs of Step 7, Step 1 and Step 2.
|
|          In addition, the EDA simulation platform will also combine the
|          output of Step 4 with the above if RX Use_Init_Output = True. 
|          When RX Init_Returns_Filter = True, this is a relatively straight
|          forward operation, but when RX Init_Returns_Filter = False, the
|          EDA simulation platform will have to take additional steps to
|          prevent the duplication of the content that is present in the
|          output of Steps 2 and/or 3 (for example by deconvolution).  This
|          is why RX Init_Returns_Filter = True is preferred when RX
|          Use_Init_Output = True.
|
|  Step 9. The output of step 8 is presented to the RX model's AMI_Getwave
|          call.  If the RX model does not include an AMI_Getwave call,
|          this step is a pass-through step, and the input to step 9 is
|          passed directly to step 10.
|
| Step 10. The output of step 9 becomes the simulation waveform output at
|          the RX decision point, which may be post-processed by the
|          simulation tool or presented to the user as is.
|
| Steps 6 though 9 can be called once or can be called multiple times to
| process the full analog waveform.  Splitting up the full analog waveform
| into multiple calls reduces the memory requirements when doing long
| simulations, and allows AMI_Getwave to return model status every so many
| bits.  Once all blocks of the input waveform have been processed, TX
| AMI_Close and RX AMI_close are called to perform any final processing and
| release allocated memory.