OSVVM – Thinking beyond constrained random

osvvm_logo_thumb What is OSVVM?

OSVVM stands for "Open Source VHDL Verification Methodology". OSVVM is a set of VHDL packages, initially developed by Jim Lewis of Synthworks. OSVVM helps you adopt modern constrained random verification techniques using VHDL.

Constraint random verification approach :

In testbenches, we generally want one each of a large set of test cases (transactions and/or sequences). Uniform randomization does not generate one each. Instead it has a significant amount of repetition. In general, uniform randomization takes O(N*LogN) randomizations to generate N unique test cases. As a result, it repeats Log N test cases. Even for small numbers such 64 test cases, constrained random will generate more than 4X more test cases than needed - actual results will vary with the randomization seed. Constrained random comes with this fundamental problem. Randomization is intended to be uniform over time. However constraint random verification has a number of benefits:

  • If you simulate longer, you generate more test vectors.
  • You may find bugs due to unexpected combinations of inputs, or extreme input values. With directed testing, it is all too easy just to test what you expect to happen, rather than trying to test what you don't expect to happen.
  • Once you have developed an automated test, it can still be used for directed testing.

Still what we need is an approach that only requires O(N) randomizations to generate N unique test cases. Generally these approaches are referred to as being Intelligent Testbenches. Indeed there are some tools out there that handle this. However, when we use a tool based approach we end up with a vendor specific solution. This removes one of the major benefits of a programming language based approach - encounter a issue (pricing or functionality) with one vendor and you can easily switch to another.

What we really need is a methodology for Intelligent Testbenches that is based on a standard language and works on numerous vendor tools.


VHDL's Open Source VHDL Verification Methodology (OSVVM). OSVVM's methodology leverages the functional coverage you must write when you are using any randomization based approach. Intelligent Coverage™, the main randomization methodology for OSVVM, randomly selects a hole in the coverage and passes this to the stimulus generation process. The stimulus generation process uses this information, perhaps refines it using any methodology (directed, algorithmic, constrained random or file based), and then generates one or more transactions to accomplish generate the item that needs covered.

OSVVM can be used in your current VHDL testbench, in part or in whole as needed.  It allows mixing of our signature “Intelligent Coverage” methodology with other verification methodologies, such as directed, algorithmic, file based, and constrained random. Don’t throw out your existing VHDL testbench or testbench models, re-use them.

There is no new language to learn. There are no specialized “OO” approaches – just plain old VHDL entities and architectures. As a result, it is accessible to RTL designers. In fact, it is our goal to make our testbenches readable to verification (testbench), design (RTL), system, and software engineers.

OSVVM works with any VHDL testbench and is particularly effective when coupled with a transaction based testbench. For us, VHDL and OSVVM are the step beyond constrained random and SystemVerilog. Maybe it is time we update VHDL's acronym to mean Verification and Hardware Design Language.

Intelligent Coverage™ Methodology :

Verification starts with a test plan that identifies all items in a design that need to be tested.  OSVVM, like other advanced methodologies, uses functional coverage to observe conditions on interfaces and within the design to validate that the items identified in the test plan have occurred.  As such, functional coverage helps determine when testing is done.

Unlike other methodologies, in OSVVM’s Intelligent Coverage methodology,  functional coverage is the prime directive – it is where we start our process.  Intelligent Coverage is done in the following steps.

  • Write a high fidelity functional coverage (FC) model
  • Randomly select a hole in the functional coverage 
  • Refine the initial randomization with sequential code 
  • Apply the refined sequence (one or more transactions) 
  • Observe Coverage

The key point of Intelligent Coverage is that we randomize using the functional coverage. Then, if necessary, we refine the randomization using sequential code and any sequence generation method, including constrained random, algorithmic, directed, or file reading methods.

OSVVM is a Low Cost Solution :

The packages are free. OSVVM works on regular VHDL simulators (such as Mentor’s ModelSim and Aldec’s Active-HDL) without additional licenses. The only special language support required is VHDL-2002 protected types and VHDL-2008 type integer_vector (for older simulators, we have a work around for this).

To learn more about OSVVM, see:

OSVVM is an open source VHDL library that is free to use (no license fees) and works with any simulator that supports VHDL-2008 (or VHDL-2002 with a little work).
What is currently in the OSVVM library is only the beginning. Over time, I will be releasing our generic scoreboard package, memory modeling package, and others.

No comments:

Post a Comment

Please provide valuable comments and suggestions for our motivation...

Popular Posts