l i a b l eh kC o m p u t i n gL a b o r a t o r y On Effective TSV Repair for 3D- Stacked ICs Li Jiang †, Qiang Xu † and Bill Eklow § † CUhk REliable Computing Laboratory Department of Computer Science & Engineering The Chinese University of Hong Kong § Cisco, CA,US

Outline Introduction Motivation TSV Redundancy Architecture Routing Heuristic for Timing Consideration Discussion & Conclusion

3D Product and To appear 3D stacked DRAM Package PCB TSV DRAM I/O Buffer RD/WR CMOS Image Sensor Interposer based 2.5D FPGA Memory on Processor More TSV More Complicated Requires manufacturing yield to be commercially viable

The Impact of 3D Stacking on Yield Stack Yield Loss MisalignmentImpurityOpenShort Leak & Delaminating Void & Break Assembly Yield Loss Leveraged by KGD test and D2W stacking

Clustered TSV Defects Assembly Yield is dramatically affected by TSV clustered faults Source: IMEC Bond pad short Unsuccessful fill

TSV Repair Schemes: Neighboring Repair 1 Spare TSV N TSV Chain 2 Spare TSVs 4 Signal TSVs Source: Kang, SAMSUNGSource: H.H-S.Lee, GATech M Spare TSV rows N x N TSV grid Source: Loi, U. Bologna

Motivation Redundancy Ratio: 1/2 To overcome: Repair faulty TSV from redundancy far apart

Motivation Problem: TSV redundancy architecture and repair algorithms

Router Based TSV Redundancy Repair faulty TSV with nearest good TSV, and continue until a redundant TSV is used M+N Spare TSVs M X N TSV Grid M+N MxN

Switch Design Direction of Rerouting Direction of Rerouting North to south, West to east (2 direction) North to south, West to east (2 direction) Bypassing signal Bypassing signal Allow multi-hop signal rerouting Allow multi-hop signal rerouting More Complex Design for more routability More Complex Design for more routability

Rerouting Scheme Edge Disjoint Paths Problem  Maximum Flow Method Repair Channel Repair Path

Problem Formulation Maximum Flow Method with 1 edge capability Maximum Flow Method with 1 edge capability Find Repair Path in Flow Graph (edge disjoint) Find Repair Path in Flow Graph (edge disjoint) Timing Constraint  Length Constraint Timing Constraint  Length Constraint Decision making in flow graph, affecting following solution Decision making in flow graph, affecting following solution Transfer the problem by finding Repair Channel Transfer the problem by finding Repair Channel Length Bonded Maximum Flow (NP-Hard) Length Bonded Maximum Flow (NP-Hard)

Heuristic Diagonal Direction Grouping Diagonal Direction Grouping Bounded BFS Search (Length Bound & Maximal Hops) Bounded BFS Search (Length Bound & Maximal Hops) Maximal Hops = 2

Experiment Setup Shifting: 2:1 Switching: 4:2 Crossbar: 8:2 router: 4x4:8,8x8:16 Vary TSV Number : 1000 ~ ~ Fault Injection: Poisson Distribution varying failure rate Poisson Distribution varying failure rate Compound Poisson Distribution varying cluster effect Compound Poisson Distribution varying cluster effect Timing Constraint: Assuming equal distances between neighboring TSVs Assuming equal distances between neighboring TSVs Length constraint: 3 – 1 times of the distance Length constraint: 3 – 1 times of the distance Comparison

Experimental Results

Conclusion Cost Effective and scalable Solution to effectively repair clustered TSV faults. From the cost perspective: Limited extra Muxes and wires Limited extra Muxes and wires To achieve the same TSV yield, the required redundant TSVs with the proposed repair scheme is much less than existing solutions To achieve the same TSV yield, the required redundant TSVs with the proposed repair scheme is much less than existing solutions

l i a b l eh kC o m p u t i n gL a b o r a t o r y Thank you for your attention !