Synthesis Dashboard

The Synthesis Dashboard provides one-click FPGA synthesis from the Visual SNN Studio. Generate Verilog from your neuron equations, then synthesise to any supported FPGA target to see resource usage and timing estimates.

No other SNN framework offers visual FPGA synthesis from a web IDE.

Quick Start

1. Write your ODE in the Equation Editor (switch to ODE mode)
2. Click IR to build the intermediate representation
3. Click SV to emit SystemVerilog
4. Switch to the FPGA tab
5. Select your target FPGA (ice40, ECP5, Gowin, Xilinx)
6. Click Synthesise for exact Yosys results, or Estimate for a quick heuristic

Workflows

Single-Target Synthesis

Select a target from the dropdown, click Synthesise. Yosys runs the target-specific synthesis pass and returns resource counts with utilisation bars.

Multi-Target Comparison

Click All Targets to run Yosys synthesis on all four supported targets simultaneously. Results appear in a comparison table showing LUTs, FFs, BRAMs, and DSPs side-by-side, so you can pick the best target for your design.

Resource Estimation (No Yosys Required)

If Yosys is not installed, click Estimate after building the IR. The estimator uses a heuristic based on IR operation count:

• Each IR op maps to ~2 LUTs + 1 FF
• LIF step op maps to ~12 LUTs + 8 FFs + 1 DSP

This gives a rough sizing before committing to a full synthesis run.

End-to-End Pipeline

Text Only

ODE equation
  → [IR button] SC Intermediate Representation
  → [SV button] SystemVerilog
  → [FPGA tab → Synthesise] Yosys resource report
  → [PnR] nextpnr timing report (ice40/ECP5 only)

From differential equation to FPGA resource estimate in seconds, from a single browser tab.

Supported FPGA Targets

Target	Device	Synth Tool	PnR Tool	LUTs	FFs	BRAMs	DSPs
ice40	iCE40 UP5K	synth_ice40	nextpnr-ice40	5,280	5,280	30	0
ECP5	LFE5U-25F	synth_ecp5	nextpnr-ecp5	24,576	24,576	56	28
Gowin	GW1N	synth_gowin	—	20,736	20,736	41	0
Xilinx	Artix-7	synth_xilinx	—	20,800	41,600	50	90

Resource Metrics

The dashboard shows four resource bars:

• LUTs — Look-Up Tables (combinational logic)
• Flip-Flops — Sequential elements (registers)
• Block RAMs — On-chip memory blocks
• DSPs — Digital Signal Processing blocks (multipliers)

Each bar shows absolute count and percentage utilisation against the target device's capacity. The multi-target comparison table shows all four metrics across all targets.

Tool Installation

The synthesis pipeline uses open-source FPGA tools:

Bash

# macOS (Homebrew)
brew install yosys nextpnr

# Ubuntu/Debian
apt install yosys nextpnr-ice40

# Windows (MSYS2)
pacman -S mingw-w64-x86_64-yosys

# Verify installation
yosys --version
nextpnr-ice40 --version

The /api/synth/tools-status endpoint reports which tools are available. The dashboard shows green/grey indicators for each tool, with version strings when available.

Target Provenance

Synthesis responses include target_provenance using the studio.synthesis-target-provenance.v1 schema. The payload records the target ID, Yosys synthesis command, optional nextpnr command and device selector, static capacity metadata, tool availability, tool version strings when available, readiness booleans, the synthesis evidence classification, and a provenance_grade claim grade. The grade is tool_backed only when every required tool for the target was detected and reported a version; otherwise it is unverified (missing tool, missing version, or no required tools). An unverified result must not be presented as release-grade PPA evidence — it records that synthesis ran without confirmed tool provenance. The serializer validates the class and the completed terminal status through the shared Studio evidence-classification contract before returning public metadata. It is path-free and suitable for operator logs and evidence bundles.

Multi-target responses additionally include target_provenance_matrix with schema studio.synthesis-target-provenance-matrix.v1. The matrix captures the same target records for every supported target, top-level synthesis evidence classification, top-level completed terminal status, an aggregate provenance_grade that is tool_backed only when every target is tool_backed, and a stable matrix_sha256 digest so operators can compare target-support evidence across runs without relying on local filesystem paths. The Studio dashboard renders that matrix after an all-target run, showing each target's device selector, synthesis readiness, PnR readiness, tool command, evidence classification, status, and shortened matrix digest without exposing host-local paths.

API Endpoints

Method	Endpoint	Description
GET	/api/synth/tools-status	Detect installed EDA tools
POST	/api/synth/run	Verilog + target → Yosys synthesis
POST	/api/synth/multi-target	Verilog → all targets comparison
POST	/api/synth/estimate	IR op count → heuristic estimate
POST	/api/synth/pnr	JSON netlist → nextpnr place & route

/api/synth/run, /api/synth/multi-target, and /api/synth/pnr execute through the Studio local worker manager. They preserve the synchronous response payloads shown below and additionally create Admin queue records with result artifacts at synthesis/result.json, synthesis/multi-target-result.json, and synthesis/pnr-result.json. On POSIX hosts, Yosys and nextpnr child processes receive configured CPU and address-space ceilings from SC_NEUROCORE_STUDIO_EDA_PROCESS_CPU_SECONDS and SC_NEUROCORE_STUDIO_EDA_PROCESS_MEMORY_BYTES; unsupported hosts keep the existing wall-clock subprocess timeouts.

GET /api/synth/tools-status

Returns availability and version for each tool:

JSON

{
  "yosys": {"available": true, "version": "Yosys 0.40"},
  "nextpnr_ice40": {"available": true, "version": "nextpnr-ice40 0.7"},
  "nextpnr_ecp5": {"available": false, "version": null},
  "firtool": {"available": false, "version": null}
}

POST /api/synth/run

JSON

{
  "verilog": "module sc_lif(...); ... endmodule",
  "target": "ice40"
}

Returns:

JSON

{
  "success": true,
  "target": "ice40",
  "resources": {"luts": 42, "ffs": 18, "brams": 0, "dsps": 0, "cells": 60, "wires": 85},
  "capacity": {"luts": 5280, "ffs": 5280, "brams": 30, "dsps": 0},
  "utilisation": {"luts": 0.8, "ffs": 0.3, "brams": 0.0, "dsps": 0.0},
  "log_excerpt": "...",
  "target_provenance": {
    "schema_version": "studio.synthesis-target-provenance.v1",
    "target": "ice40",
    "synthesis_command": "synth_ice40",
    "pnr_tool": "nextpnr-ice40",
    "device": "up5k",
    "synthesis_ready": true,
    "pnr_ready": true,
    "provenance_grade": "tool_backed",
    "evidence_classification": "synthesis",
    "status": "completed",
    "tools": [
      {"key": "yosys", "executable": "yosys", "role": "synthesis", "available": true, "version": "Yosys 0.40"}
    ]
  }
}

POST /api/synth/multi-target

JSON

{"verilog": "module sc_lif(...); ... endmodule"}

Returns synthesis results for all supported targets:

JSON

{
  "targets": {
    "ice40": {"success": true, "target": "ice40", "resources": {...}, ...},
    "ecp5": {"success": true, "target": "ecp5", "resources": {...}, ...},
    "gowin": {"success": true, ...},
    "xilinx": {"success": true, ...}
  },
  "target_provenance_matrix": {
    "evidence_classification": "synthesis",
    "provenance_grade": "tool_backed",
    "schema_version": "studio.synthesis-target-provenance-matrix.v1",
    "status": "completed",
    "matrix_sha256": "<64 lowercase hex characters>",
    "targets": {"ice40": {...}, "ecp5": {...}, "gowin": {...}, "xilinx": {...}}
  },
  "supported": ["ice40", "ecp5", "gowin", "xilinx"]
}

POST /api/synth/estimate

Quick heuristic estimate without running Yosys:

JSON

{"ir_op_count": 10, "target": "ice40"}

Returns:

JSON

{
  "target": "ice40",
  "estimated": true,
  "resources": {"luts": 32, "ffs": 18, "brams": 0, "dsps": 1},
  "capacity": {"luts": 5280, "ffs": 5280, "brams": 30, "dsps": 0},
  "utilisation": {"luts": 0.6, "ffs": 0.3, "brams": 0.0, "dsps": 0.0}
}

POST /api/synth/pnr

Place-and-route a Yosys JSON netlist (ice40 and ECP5 only):

JSON

{"json_path": "/path/to/design.json", "target": "ice40"}

Returns timing analysis:

JSON

{
  "success": true,
  "max_freq_mhz": 48.3,
  "critical_path": "clk -> neuron.v_reg -> spike_out",
  "log_excerpt": "..."
}