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DATC RDF Calibrations (2021)

This repository provides calibrations for four basic electrical analyses using publicly-available enablements (ASAP7, NanGate45, SKY130HD, and SKY130HS):

1. Timer calibration data for static timing analysis
2. RC parasitic calibration data
3. Static IR drop estimation

Our hope is that these calibration datasets will help boost the research community's advancement along the axes of accuracy, turnaround time, and capacity for these fundamental analyses that inform IC physical implementation.

Contributions

• Thanks to Jagang Lee (POSTECH) for providing all OpenROAD SP&R calibration testcases!
• Thanks to Vidya Chhabria (UMN) for providing the IR drop simulation and JSONs!

Calibration Data: Overview (43 testcases)

Each calibration data consists of the following files:

• Timing and RCX calibrations:

  • *.def: DRV-free routed DEF using OpenROAD-flow-scripts, commit: affb7b.
  • *.v: Verilog from routed DEF.
  • *.sdc: Timing constraint file. Contains clock periods.
  • *.spef: SPEF file from routed DEF.
  • *5_worst.json: Top 5 worst timing paths from timing report.
  • *5_worst.json.rpt : Top 5 worst timing report as OpenSTA format.
  • *endpoint_slacks.json: Endpoints slack from timing report.

• IR drop calibration:

  • *_ir.[VDD/VSS].json: Per-instance static IR drop.
  • *.vsrc.json: VDD and VSS Voltage source location files.

Timer Calibration Data

Our initial data compilation uses routed DEFs produced by the OpenROAD flow in SKY130HD, SKY130HS, and NanGate45 enablements. Golden calibration data is abstracted and anonymized using a 5-worst JSON format, which we use to hold block-level worst (negative) slack, total negative slack, and number of failing endpoints (i.e., standard WNS, TNS and FEP metrics), along with detailed information for the top-5 worst timing paths (including arc delays and pin arrival times). We provide a timing report viewer that reads 5-worst JSON-formatted data and prints out a timing report in the OpenSTA tool's report format. To facilitate other calibrations of interest, we also propose an endpoints JSON format, which captures setup slack values at every flip-flop D pin. With these, we can compare the endpoint slacks from OpenSTA with calibration endpoint slack values.

JSON Format Description

5 Worst JSON

• Contains the following

  • Block-level worst (negative) slack (WNS)
  • Block-level total negative slack (TNS)
  • Block-level number of failing endpoints (FEP)
  • Detailed information for the top-5 worst timing paths (including arc delays and pin arrival times)

• Example

    {
      "summary": {
      "WNS": "-0.230",
      "TNS": "-10.560",
      "FEP": "139",
      "tech": "freepdk45",
      "design": "aes_cipher_top"
    },
    "detail": {
      "top1": {
        "endPoint": "_28884_/D",
        "endPointStatus": "Rising",
        "startPoint": "_28827_/Q",
        "startPointStatus": "Falling",
        "pathGroup": "reg2reg",
        "setupTime": "0.039",
        "clockPeriod": "1.000",
        "pathRAT": "1.310",
        "pathAAT": "1.541",
        "slack": "-0.230",
        "pathList": [
        {
          "pin": "clk",
          "status": "Rising",
          "net": "clk",
          "masterType": "",
          "delay": "",
          "AAT": "0.000"
        },
        {
          "pin": "clkbuf_0_clk/A",
          "status": "Rising",
          "net": "clk",
          "masterType": "BUF_X4",
          "delay": "0.009",
          "AAT": "0.009"
        },
        ...
  

  • summary: summary of the given design
    • WNS: Block-level worst (negative) slack (WNS)
    • TNS: Block-level total negative slack (TNS)
    • FEP: Block-level number of failing endpoints (FEP)
    • tech: Technology
    • design: Design name
  • detail: Detailed information for the top-5 worst timing paths
    • topN : N-th path (N: 1~5)
      • endPoint: Endpoint. InstanceName + "/" + PinName
      • endPointStatus: Endpoint status. Rising or Falling
      • startPoint: Startpoint. InstanceName + "/" + PinName
      • startPointStatus: Startpoint status. Rising or Falling
      • pathGroup: Path group. reg2reg
      • setupTime: Setup time
      • clockPeriod: Clock period
      • pathRAT: Path Required Arrival Time (RAT)
      • pathAAT: Path Actual Arrival Time (AAT)
      • slack: Slack in current path
      • pathList: Detailed path list
        • pin: pin. InstanceName + "/" + PinName
        • status: Pin status. Rising or Falling,
        • net: Net where pin is located
        • masterType: Master cell where pin is Located
        • delay: Delay
        • AAT: Actual Arrival Time (AAT) in pin

5 Worst JSON Timing Report Converter

• Timing report viewer [link]

  • Takes 5 Worst JSON and print out a timing report as OpenSTA style

  • Example usage

    python3 timing_report_converter.py aes_cipher_top_5_worst.json
    

  • Example output

    =========================================================
          Summary
    =========================================================
    WNS: -0.230
    TNS: -10.560
    FEP: 139
    
    ---------------------------------------------------------
      top1 worst timing path
    ---------------------------------------------------------
    Startpoint: _28827_/Q (Falling)
    Endpoint: _28884_/D (Rising)
    Path Group: reg2reg
    
      Delay    Time   Description
    ---------------------------------------------------------
       0.00    0.00 ^ clk
       0.01    0.01 ^ clkbuf_0_clk/A (BUF_X4)
       0.03    0.04 ^ clkbuf_0_clk/Z (BUF_X4)
       0.00    0.04 ^ clkbuf_1_0_0_clk/A (CLKBUF_X1)
       0.04    0.07 ^ clkbuf_1_0_0_clk/Z (CLKBUF_X1)
       0.00    0.07 ^ clkbuf_1_0_1_clk/A (CLKBUF_X1)
       0.06    0.13 ^ clkbuf_1_0_1_clk/Z (CLKBUF_X1)
    ...
    

Endpoints Slack JSON

• Contains setup slack values at every flip-flop D pin.

     "tech": "freepdk45",
      "design": "aes_cipher_top",
      "pins": [
        "_28572_/D",
        "_28573_/D",
        ...
       ],
      "slacks": [
        "0.648",
        "0.731",
        ...
      ]
  

  • tech: Technology
  • design: Design name
  • pins: Endpoints pin lists
  • slacks: Corresponding endpoints slacks

RCX Calibration Data

RCX calibration data is also provided as Standard Parasitic Exchange Format (SPEF) for each testcase.

Static IR Drop Calibration Data

The static IR drop calibration data is currently available for the SKY130HD and SKY130HS enablement. Golden static IR drop data is anonymized and made available in a JSON format. The location of voltage sources which these golden per-instance IR drop values are obtained are also anonymized and reported in a JSON format. The IR drop calibration numbers were obtained using the same .def, .v, .sdc, and .spef as the timing calibration results.

JSON Format Description

The golden IR drop reports are anonymized in the JSON format described below.

File: <design_name>_ir.[VDD/VSS].json

There are two sections in this file:

• Summary: lists the design_name, technology, voltage values, timing corner, and a summary of the worst-case IR drop in the wir section. The wir section has the worst-case static IR drop value, the metal layer on which it occurs, and the instance name with the worst-case IR drop.
• Detail: provides a list of instances in the design along with its corresponding voltage values.

Example of the summary and detail section of the JSON is shown below:

  "summary": {
    "design": "design_name",
    "powerNet": "net_name",
    "tech": "sky130hd",
    "timingCorner": "tt_025C_1v80",
    "vdd": 1.8,
    "vss": 0,
    "wir": {
      "instanceName": "_28766_",
      "ir": 0.031,
      "layer": "met1",
      "voltage": 1.769
    }
  },
  "detail": {
    "instanceList": [
      "_28766_",
      "FILLER_170_1364",
      "FILLER_170_1362",
      "FILLER_170_1358"
    ],
    "voltages": [
      1.769,
      1.769,
      1.7691,
      1.7691
    ]
  }

File: <design>.vsrc.json

This is an input file which is necessary for static IR drop analysis. It contains the location of the voltage sources for both VDD and VSS. The JSON described below creates an anonymized representation for specifying these inputs. It consists of two sections:

• Summary: lists design name, the number of VDD/VSS sources, the top-most metal layer on which these voltage sources are attached to, and the technology.
• Detail: provides details of the name of the voltage source, its type (either VDD/VSS) and its location.

Example of this file is shown below:

  "summary": {
    "design": "design_name",
    "numVddSrcs": 1,
    "numVssSrcs": 1,
    "tech": "sky130hd",
    "vdd": 1.8,
    "voltageSrcMetalLayer": "met4",
    "vss": 0
  },
  "detail": {
    "voltageSrcList": [
      {
        "type": "VDD",
        "voltageSrcName": "VDD100",
        "xLocation": 12,
        "yLocation": 12
      },
      {
        "type": "VSS",
        "voltageSrcName": "VSS101",
        "xLocation": 544,
        "yLocation": 12
      }
    ]
  }

Adding Noise

We provide Python scripts to introduce noise in the calibration data to enable obfuscations.

• add_timing_noise.py: reads 5-worst and endpoint-slack JSON, and adds noises.
• add_power_noise.py: reads VDD/VSS IR-drop JSON, and adds noises.

To find the details of the noise introduction method, please refer to our ICCAD 2021 paper:

J. Chen, I. H.-R. Jiang, J. Jung, A. B. Kahng, S. Kim, V. N. Kravets, Y.-L. Li, R. Varadarajan and M. Woo, "DATC RDF-2021: Design Flow and Beyond", Proc. ACM/IEEE International Conference on Computer-Aided Design (ICCAD), 2021. (Invited)

Further Resources

In an effort to drive PDN analysis and synthesis research, the following repository contains PDN benchmarks in SPICE format (similar to the IBM PG benchmarks in a 45nm technology with open-source designs using both OpenROAD flow and commercial tools.

• https://github.com/PDN-BeGAN/BeGAN-benchmarks

In addition, in an attempt to generate a larger benchmark set for ML calibrations, the above repo contains 10 synthetic current maps generated by GANs (BeGAN benchmarks). These benchmarks maintain characteristic traits of real current maps while being sufficiently different.

Citation

Please cite the following paper

• J. Chen, I. H.-R. Jiang, J. Jung, A. B. Kahng, V. N. Kravets, Y.-L. Li, S.-T. Lin and M. Woo, "DATC RDF-2020: Strengthening the Foundation for Academic Research in IC Physical Design", Proc. IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2020. (Invited)
• J. Chen, I. H.-R. Jiang, J. Jung, A. B. Kahng, S. Kim, V. N. Kravets, Y.-L. Li, R. Varadarajan and M. Woo, "DATC RDF-2021: Design Flow and Beyond", Proc. ACM/IEEE International Conference on Computer-Aided Design (ICCAD), 2021. (Invited)