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SHAKTI: An Open-Source Processor Ecosystem

5.2 SHAKTI Lock Step Verification

While the previous section describes an automated way of generating tests, there still exists the huge time penalties of running these simulations. While the Bluesim environment, which executes the cycle- accurate C model of the design, does accelerate simulation by nearly 8-10x than standard verilog RTL simulators, the simulation times are still high for large applications. Additionally, in order to create the state-dump a file-io is required which can also consume significant time during simulations. Another issue with the state-matching scheme mentioned in Figure-4 is that it is not real-time. Thus, a bug which occurs much early in the simulation can only be detected when the simulation completes or is terminated. This increases the turn-around time for bug detection and fixes.

SHAKTI offers, the SLSV (SHAKTI Lock Step Verification) framework which can address the challenges specifically mentioned above. SLSV is a customizable verification framework that offers designers a platform to perform dynamic verification of their designs over a variety of configurations. SLSV can be used across design stages – right from RTL to Silicon – with the appropriate interfaces as shown in

eq17Fig. 5. Targets in today‘s Verification Ecosystem

SLSV provides a robust framework which allows the user to execute multiple implementation of the RISC-V ISA and check for compliance against each other. These implementations can be either instruction set simulators like Spike, or cycle accurate simulators like the c-class Bluesim executable, or the generated verilog and even FPGA/ASIC hardware implementations. In fact, SLSV can also integrate the formal model of the ISA and provide a formal validation the design under verification. SLSV uses directed tests or AAPG outputs as stimulus to instances and checks the state variables of different instances at the end of each instruction.

SLSV is independent of the interface used by the implementation to communicate the state-variables. It can use simple file-io to interact with simulation models or use JTAG sequences to interact with FPGA platforms and even use customized trace protocols to collect more information. Other than merely comparing states across implementations, SLSV also offers the potential of providing a test- coverage metric, event handlers, event distributors, etc. as shown in figure-5.2. SLSV is thus aimed at not improving verification speeds, but also providing the user a constructive feedback on the state variables being accessed by the current stimulus.

eq17Fig. 6. SLSV(on a host PC) interfaced with a DUV and an instruction retirement level granularity equivalent golden model for Tandem Verification.


6. Auxiliary RISC-V Tools

The previous few sections describe the essential tools required to build and verify a processor. In this section we discuss one particular tool, called RiTA (RISC-V Trace Analyzer) which captures various statistics of a given application post its execution on a platform. Such a tool is important from the point of view of analyzing custom workloads and identifying scenarios either in the software stack or the hardware stack than can accelerate the program and provide better metrics. For eg, in order to reduce the code-density of the particular application, it is necessary to identify the sequence of code which is repeatedly accessed and check if a fused macro-op can be used to reduce the code-space.

RiTA takes a post-execution trace of a program and provides the user with the following statistics:

(1) Instruction histogram – number of times each instruction opcode was executed. (2) Register histogram – number of times each register was read/written.
(3) Memory histogram – number of times a particular data segment address was read/written.
(4) Branch statistics – number branches, taken branches, forward branches, backward branches, etc. (5) Loop statistics – number of loops, size of a loop, iterations within a loop, etc.
(6) Sequence statistics – Identify whether a user-defined sequence of dependent instructions exists in the trace or not and also the number of times it has occurred.

RiTA is designed as a tiered application. This structure helps to keep different parts of the system de-coupled and thus helps in extensibility and plugging it into other frameworks. The first layer of RiTA is the trace source parser. The parser plays the role of reading in the input data and extracting the necessary details from it. In the current architecture the parser accepts a log file as an input. By using regular expression matching, we are able to extract the machine hex which corresponds to each instruction. This machine hex is then passed on to the next layer which is the instruction parser.

The machine hex opcode can be used to extract the necessary bit-fields like opcode, target regis- ter, source registers and then use this information in further statistics. The final layer is the post- processing module. The post-processing modules are all independently written so users can share the modules they write. Creating a new post-processing module is as easy as copying an existing one and modifying the source code to match your implementation.

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