// SILICON ROADMAP — VERSION 1.0 — MARCH 2026

QUDM PROCESSOR

Quantitative Universal Diffusion Model · NPU

The world's first diffusion-native neural processing unit. From PyTorch prototype to custom silicon in six months. 150 int4 TOPS at 5W. Code generation at the speed of thought.

150 int4 TOPS

3nm TSMC Node

30 TOPS/Watt

Q4 '26 Launch

SCROLL TO EXPLORE

// PHASE ONE · WEEKS 1–4

Model Optimization

Goal: Production-ready 4-bit QUDM model for NPU deployment

// WEEK 01

Quantization & Validation

Complete 4-bit PTQ pipeline via torchao → ONNX → Qualcomm AI Engine Direct SDK
Calibration dataset: 20+ programming languages + multilingual natural language (128–512 samples per domain)
Target: less than 5% perplexity degradation, 4k tokens/sec on Snapdragon X Elite
Validate int4 weight accuracy across C#, Python, Rust, HLSL shader DSLs
Profile memory footprint: target 300MB quantized model on-device

↳ qudm_4bit_npu.qmodel · 300MB · NPU validated

// WEEK 02

Edge Deployment

.NET MAUI native bindings for Snapdragon X Elite and Ryzen AI 300 NPU backends
Real-world test scenarios: music production (HLSL synth gen), game AI (live NPC dialogue), shader code completion
LoRA fine-tunes: C#, Swift, Rust, Lua, and domain-specific shader DSLs
Latency profiling: measure first-token latency vs batch throughput trade-offs
Power envelope measurement on Snapdragon X Elite devkit (target: under 8W sustained)

↳ MAUI app demo · live QUDM inference on consumer hardware

// WEEKS 03–04

Performance Scaling

Fuse diffusion denoising steps from 8 → 4 via NPU kernel fusion and schedule optimization
MAMBA-2 structured sparsity: exploit SSM recurrence for further int4 compression
VAR-aligned int4 quantization for consistent visual token generation
Multi-platform benchmark: H100 (training throughput), Jetson Orin (edge inference), Akida 2 (ultra-low power sub-1W)
Generate throughput regression report across all target hardware

↳ QUDM v1.0 production model + full throughput benchmark report

// PHASE TWO · WEEKS 5–12

Architecture Definition

Goal: Custom QUDM NPU specification & RTL development

// IP BLOCK SPECIFICATION

CORE ARRAY	128×128 MAMBA-2 SSM MAC (int4)
DIFFUSION ENGINE	64-step parallel denoiser · cosine schedule
ON-CHIP SRAM	16 MB · 512 GB/s bandwidth
MEMORY I/F	LPDDR5X · up to 64 GB/s external BW
CHIP I/O	PCIe Gen5 x16 + LPDDR5X
POWER CONFIG	5–15W configurable TDP
MOBILE CLOCK	2.5 GHz boost
DATACENTER CLOCK	4.0 GHz boost
PEAK PERFORMANCE	150 int4 TOPS · 4× Snapdragon X Elite

// RTL DEVELOPMENT PLAN

LANGUAGE	SystemVerilog (RTL) · UVM (testbench)
CORE MODULE	MAMBA matrix-multiply accelerator block
DIFFUSION PATH	Noise schedule → denoise → token projection
STATE UPDATE	SSM recurrence loop · pipelined int4 MACs
TESTBENCH	Random code generation accuracy validation suite
SYNTHESIS	Synopsys VCS simulation · Cadence Genus synthesis
TIMING CLOSURE	Target: PVT corners at 2.5 GHz / 0.75V
DFT	Scan chains · BIST for memory arrays
IP LICENSING	ARM Cortex-A78 · MAMBA SSM IP block

[MAC]

MAMBA SSM Array

State-space model recurrence mapped to systolic int4 MAC grid. 128×128 tiles enable full MAMBA-2 matrix projection in a single clock-aligned burst.

[DNZ]

Parallel Denoiser

Hardware-accelerated cosine noise schedule controller. 64-step denoising unrolled across dedicated pipeline stages — no CPU round-trips.

[MEM]

16MB SRAM Cluster

Multi-bank scratchpad with 512 GB/s internal bandwidth. Feeds the MAC array without external memory stalls for sequences under 4k tokens.

[I/O]

PCIe Gen5 Interface

Full bidirectional host connectivity. Supports both discrete PCIe add-in card and embedded SoC configurations. LPDDR5X for mobile variants.

// PHASE THREE · MONTHS 4–9

Fabrication & Silicon

Goal: Silicon validation from first test chip to full production SoC

// MPW1 · MONTH 4

Test Chip

TSMC 5nm · 1mm² die · 10k gates

QUDM core only — no peripheral logic
Ring oscillator array for process characterization
MAMBA throughput validation at speed
Diffusion convergence across 4 cosine schedule configs
Leakage + dynamic power characterization at PVT

↳ Silicon: MAMBA throughput confirmed · diffusion convergence ✓

// MPW2 · MONTH 7

Full SoC

28nm (cost node) · 100mm² die

QUDM NPU core + ARM Cortex-A78 application processor
LPDDR5 memory controller + PCIe Gen4 interface
Full .NET MAUI software stack running end-to-end
Board bring-up with reference design EVB
Functional coverage: code gen, shader synthesis, NPC dialogue

↳ SoC: full stack running · EVB in developer hands

// PRODUCTION · MONTH 10

QUDM-1

TSMC 3nm · 250mm² die

8× QUDM cores — 1.2k int4 TOPS aggregate
CoWoS-S advanced packaging with HBM3 option
Dual power domains: 5W mobile / 25W datacenter
85% yield target at 2.5 GHz nominal
GlobalFoundries 22nm automotive variant for ADAS/robotics

↳ Production silicon: 1.2k TOPS · 85% yield · Q4 launch-ready

// TEST & VALIDATION PLAN

PRE-SILICON EMULATION	Xilinx Versal FPGA · full RTL emulation at 250 MHz
POST-SILICON ACCURACY	Code generation benchmark: HumanEval, MBPP, QUDM-code-500
POWER TARGET (MOBILE)	5W · sustained inference on devkit
POWER TARGET (DC)	25W · batch inference · datacenter SKU
YIELD TARGET	85% functional @ 2.5 GHz · TSMC 3nm
MANUFACTURING TEST	Amkor + ASE · ATE with custom QUDM test vectors
PACKAGING	TSMC CoWoS-S · Intel EMIB for chiplet variants

// PHASE FOUR · MONTHS 10–12

Ecosystem & SDK

Goal: Full software stack, developer tools, and model zoo for day-one partners

[SDK]

Neural Engine Direct

PyTorch → RTL compilation pipeline. Developers write standard PyTorch; QUDM Neural Engine Direct compiles directly to NPU instruction set with zero framework overhead.

[CMP]

TVM QUDM Compiler

Apache TVM backend extended with MAMBA and diffusion-specific optimization passes. Auto-tunes kernel configurations across QUDM core counts and memory layouts.

[RT]

Cross-Platform Runtime

.NET MAUI (Windows/Mac/iOS/Android), Linux system daemon, and Android NNAPI delegate. Single unified API surface across all deployment targets.

[ZOO]

Model Zoo

Day-one pre-quantized models: Mercury 2, Llama 4, QUDM-base, and 10+ domain-specific LoRAs. All validated and signed for secure deployment.

[SEC]

Secure Enclave

Hardware-level model signing and encrypted weights at rest. QUDM silicon includes a dedicated security processor for IP protection and enterprise compliance.

[DEV]

Developer Console

Real-time performance profiler, power trace analyzer, and kernel inspector. Surfaces NPU utilization, diffusion step timing, and memory pressure in one dashboard.

// PHASE FIVE · Q4 2026

Market Launch

Goal: Four product SKUs targeting mobile, edge, and datacenter markets

$999

QUDM-DEVKIT

Snapdragon X Elite + QUDM Co-Processor

Full QUDM NPU co-processor board
Snapdragon X Elite host platform
Complete SDK + development toolchain
MAUI reference application suite
Priority partner support access
Target: AI application developers

$199

QUDM-MOBILE

5W always-on · music + game AI

Ultra-low-power 5W sustained TDP
Always-on inference capability
Music production: HLSL synth generation
Game AI: real-time NPC dialogue
LPDDR5 integrated variant
Target: creative hardware + gaming

$499

QUDM-EDGE

Jetson form-factor · robotics & ADAS

Jetson-compatible carrier board
GlobalFoundries 22nm automotive grade
AEC-Q100 qualification path
ROS 2 + MAUI runtime stack
Extended temp range: −40°C to 125°C
Target: robotics, drones, ADAS

$2,999

QUDM-PRO

8-core · datacenter training + inference

8× QUDM cores · 1.2k int4 TOPS
25W datacenter power profile
PCIe Gen5 x16 add-in card
CoWoS-S advanced packaging
Batch inference + fine-tuning support
Target: cloud, enterprise, research labs

// CRITICAL PATH & BUDGET

Total Investment: $2.1M Seed Round

Phase breakdown · USD estimates TOTAL RAISE TARGET: $2,000,000

Phase	Duration	Cost Estimate	Key Dependencies	% of Total
P1 · Model Optimization	4 weeks	$50,000	Training cluster access (H100 hours)	2.4%
P2 · Architecture	8 weeks	$250,000	ARM Cortex-A78 IP license · MAMBA IP	11.9%
P3 · Tapeout × 2 + Production	20 weeks	$1,500,000	TSMC MPW slot (5nm) · GF 22nm slot	71.4%
P4 · Ecosystem & SDK	8 weeks	$200,000	Engineering team · toolchain licenses	9.5%
P5 · Launch	4 weeks	$100,000	Marketing · partner onboarding · events	4.8%

// IMMEDIATE ACTION ITEMS

This Week's Critical Path

Download Qualcomm AI Engine Direct SDK Install and configure the Qualcomm SDK for Snapdragon X Elite NPU targeting. Verify int4 model ingestion pipeline end-to-end.

Run QUDM 4-bit Benchmark on X Elite Devkit Execute calibration pass on 128 code samples. Record tokens/sec, perplexity, and power draw. Document baseline for Week 1 deliverable.

Contact TSMC MPW for 5nm Slot (Q3 2026) Submit intent form for Multi-Project Wafer run. Confirm design rule check (DRC) requirements for 5nm N5 process node.

Secure $2M Seed Funding — Chip Tapeout Tapeout funding is the critical path gate. Initiate outreach to deep-tech and semiconductor-focused seed funds. Use this roadmap as the pitch artifact.