🔌 Module 5 · Chip Hardware · Chapter 5.14 · 9 min read

Y1 / Y10 / Y100 Comparison

SIDRA YILDIRIM generation roadmap — six years of plan in one table.

Prerequisites

5.4 — YILDIRIM Chip Architecture

What you'll learn here

Compare Y1, Y10, Y100 spec by parameter
State the technology jumps per generation
Track TOPS, TOPS/W, area, energy evolution
Identify which generation fits which market
Grasp the Y1000 vision

Hook: 6-Year Roadmap, One Page

The SIDRA YILDIRIM family:

Y1 (2026-2027): workshop prototype → product.
Y10 (2029-2030): datacenter expansion.
Y100 (2031-2033): datacenter standard + edge.
Y1000 (2035+): vision, photonic + bio-compatible.

This chapter lays them all side by side.

Intuition: Each Generation 10× Larger

Metric	Y1	Y10	Y100	Y1000
Production year	2026	2029	2031	2035+
CMOS process	28 nm	14 nm	7 nm	5 nm + photonic
Cell size	100 nm	70 nm	28 nm	14 nm + 3D
Bits/cell	8	10	12	16
Memristor count	419M	10B	100B	1T
Weight capacity	419 MB	12 GB	150 GB	2 TB
Crossbar size	256²	512²	1024²	4096²
Crossbar count	6400	40K	100K	1M
Analog TOPS	30	300	3000	30000
TOPS/W	10	100	300	1000
TDP	3 W	30 W	100 W	100 W
Die area	100 mm²	200 mm²	400 mm²	800 mm² (3D)
Packaging	FC-BGA	CoWoS	CoWoS+3D	wafer-scale

Every 2-3 years a new generation, performance 10×, efficiency 3-10×.

Formalism: Generation-by-Generation Detail

L1 · Başlangıç

Y1 (in production):

28 nm CMOS substrate + 100 nm HfO₂ memristor BEOL.
One crossbar 256×256 = 65K cells.
6400 crossbars = 419M memristors.
30 TOPS analog, 3 W TDP.
Inference focus (training on GPU).
Market: edge AI, embedded, IoT.

Y10 (in development):

14 nm CMOS + 70 nm cell.
Crossbar 512×512 = 262K cells.
40K crossbars = 10B memristors.
300 TOPS, 30 W.
Hybrid training (last layer).
1S1R 3D-stack 4 layers.
TDC ADC standard.
HBM3 integration (CoWoS).
Market: datacenter inference, high-perf edge.

Y100 (planned):

7 nm CMOS + 28 nm cell.
Crossbar 1024×1024 = 1M cells.
100K crossbars = 100B memristors.
3 POPS, 100 W.
Full analog backward (training).
1S1R 8-layer 3D.
Photonic interconnect.
On-chip STDP learning.
Market: GPT-class inference, datacenter standard.

Y1000 (long horizon):

5 nm CMOS + 14 nm cell + 2D material.
Crossbar 4096² = 16M cells.
1M crossbars = 1T memristors.
30 POPS, 100 W (1000 TOPS/W).
Photonic + electronic hybrid.
Bio-compatible organic generation.

L2 · Tam

Process evolution:

28 nm → 14 nm: TSMC standard transition, ~2 years.
14 nm → 7 nm: big jump, EUV required.
7 nm → 5 nm: marginal, near-limit.

SIDRA follows the supplier (TSMC) for these. BEOL memristor development runs in parallel.

Crossbar size growth:

256 → 512 → 1024 → 4096. Each step is 4× cells. But IR drop and sneak path grow → design improvements in lockstep:

Y1: 256, 1T1R.
Y10: 512, 1T1R + early 1S1R.
Y100: 1024, 1S1R 3D.
Y1000: 4096, 1T (selectorless) + 3D-stack.

Performance evolution:

Y1 30 TOPS → Y100 3 POPS = 100×. 100× in 6 years = beyond classical Moore’s Law (which is 2-3 years per 2×). Compute-in-memory advantage.

Y100 is ~3× over H100 inference (H100 ~1 PFLOPS sustained AI).

Market segmentation:

Market	Y1	Y10	Y100
Mobile/IoT	✓	-	-
Smart camera	✓	✓	-
Embedded	✓	✓	-
Edge server	-	✓	✓
Datacenter inference	-	✓	✓
Datacenter training	-	-	✓

Y1 = small market (edge). Y10 = mid. Y100 = big.

Revenue estimate:

Y1: 100K chips/year × $50 =$ 5M/year. Y10: 1M chips/year × $500 =$ 500M/year. Y100: 10M chips/year × $2000 =$ 20B/year.

(Compare: NVIDIA’s 2024 datacenter revenue ~$50B/year.)

L3 · Derin

Tech transitions (Y1 → Y10):

CMOS: 28 → 14 nm. Foundry transition.
Memristor: HfO₂ → HfAlO. Endurance 10⁶ → 10⁷.
Cell: 1T1R → add 1S1R. 3D-stack begins.
ADC → TDC: ~60% area saved.
Hybrid training: last layer on SIDRA.

Y10 → Y100:

CMOS: 14 → 7 nm. EUV.
Memristor: HfAlO + HZO ferroelectric hybrid.
3D stack: 4 → 8 layers.
Photonic interconnect: wafer-scale.
Online learning: hardware STDP.

Y100 → Y1000:

2D material: MoS₂, hBN heterostructure.
Wafer-scale: Cerebras-style single wafer.
Bio-compatible organic: PEDOT:PSS synapse.
Superconducting option: 4 K cryogenic (special apps).

Risk points:

Y10: 1S1R production maturity. NbOx OTS endurance.
Y100: photonic on-chip integration (still prototype).
Y1000: bio-compatible material stability.

Türkiye strategic position:

Y1: workshop, small batch. Türkiye design + workshop production. Y10: mini-fab. Feasible in Türkiye (~ $200M investment). Y100: full fab. ~$ 5B. Can Türkiye? Political call. Y1000: world standard. Continues if Türkiye is in at Y100.

SIDRA team timeline:

2024-2026: Y1 tape-out + production.
2026-2028: Y3 prototype (Y1 improvements).
2028-2030: Y10 tape-out + production.
2030-2033: Y100 tape-out.
2033+: Y1000 prototype.

Experiment: Three-Generation GPT-3 Inference

GPT-3 175B params, FP16 = 350 GB. One inference 350 GFLOP.

Y1: capacity 419 MB → GPT-3 doesn’t fit. Multiple chips needed (~840 Y1). Impractical.

Y10: capacity 12 GB → multiple chips (29 Y10). Cluster server.

Y100: capacity 150 GB → 3 Y100 in parallel. Single server.

Y1000: capacity 2 TB → 1 chip. Datacenter.

Per-token inference time:

Y1: 350 GFLOP / 30 TOPS = 12 ms (single-chip insufficient).
Y10: 350 / 300 = 1.2 ms.
Y100: 350 / 3000 = 0.12 ms.
Y1000: 350 / 30000 = 12 µs.

1000-token energy:

Y10: 3 W × 1.2 s = 3.6 J.
Y100: 100 W × 0.12 s = 12 J.
H100 compare: ~1.4 ms × 700 W = 1 J/token, 1000 tokens = 1 kJ. SIDRA 100×+ more efficient.

TCO (Total Cost of Ownership) 5 years, datacenter:

1000 H100: $50M chips +$ 20M power (5 years) = $70M.
100 Y100: $5M chips +$ 2M power = $7M.

SIDRA is 10× cheaper for datacenter inference.

Quick Quiz

1/6Y1 → Y100 performance multiplier?

Lab Exercise

SIDRA annual production-volume planning.

Market estimates:

Edge AI 2026: $5B,$ 50/device, 100M device potential.
Datacenter inference 2030: $50B,$ 5K/server, 10M servers.
Semiconductor market 2035: $1T, 20% AI =$ 200B.

Questions:

(a) Y1 100K chips/year — workshop capacity? (b) Y10 1M chips → mini-fab (~ $200M) needed? (c) Y100 10M chips → full fab (~$ 5B)? (d) Years for Türkiye to reach 1% of global AI chip market? (e) SIDRA valuation in 2030?

Solutions

(a) Workshop capacity: 200 mm wafer, 38 dies/wafer, 70% yield = 27 chips/wafer. 100K/year = 3700 wafers/year = 10 wafers/day. Workshop capacity sufficient (mid-small design workshop).

(b) Y10 1M chips = 37K wafers/year = 100 wafers/day. Mini-fab (~$200M) supports it. Türkiye-feasible (TÜBİTAK + ASELSAN partnership).

(d) Türkiye 1% = ~ $2B/year (2035 market).$ 500M Y10-based, $20B/year via Y100. Achievable between 2030-2035.

(e) SIDRA 2030 valuation: $5B (Y10 products), 2035$ 20B (with Y100). Comparable to modern AI chip companies (Cerebras $4B, Mythic$ 200M, Rain $80M private). Important for Türkiye’s leadership.

Cheat Sheet

Y1: 30 TOPS, 3W, 419M memristors, 28 nm. Edge.
Y10: 300 TOPS, 30W, 10B, 14 nm. Datacenter inference.
Y100: 3 POPS, 100W, 100B, 7 nm. GPT-class.
Y1000: 30 POPS, 100W, 1T, 5 nm + photonic + bio.
Process: 28 → 14 → 7 → 5 nm + 2D.
Memristor: HfO₂ → HfAlO → +HZO → 2D heterostructure.
Crossbar: 256² → 512² → 1024² → 4096².
Market: edge → datacenter → GPT.

Vision: Türkiye's Neuromorphic 2035

At the Y1000 horizon (2035-2040):

3-5 different SIDRA variants produced in Türkiye (mobile, automotive, medical, space, industrial).
$20-50B/year AI chip exports.
50K+ AI engineers employed.
100+ university research groups.

Path:

2026-2028: Y1 product, workshop expansion.
2028-2030: Y3 prototype, mini-fab build.
2030-2033: Y10 production, datacenter market.
2033-2037: Y100 production, world-market share.
2035+: Y1000 vision.

Prerequisites

What you'll learn here

🪝 Hook: 6-Year Roadmap, One Page

🧭 Intuition: Each Generation 10× Larger

📐 Formalism: Generation-by-Generation Detail

🧪 Experiment: Three-Generation GPT-3 Inference

📝 Quick Quiz

🛠️ Lab Exercise

🗂️ Cheat Sheet

🔮 Vision: Türkiye's Neuromorphic 2035

📚 Further Reading