Design for pre-bond testability in 3D integrated circuits

In this dissertation we propose several DFT techniques specific to 3D stacked IC systems. The goal has explicitly been to create techniques that integrate easily with existing IC test systems. Specifically, this means utilizing scan- and wrapper-based techniques, two foundations of the digital IC test industry. First, we describe a general test architecture for 3D ICs. In this architecture, each tier of a 3D design is wrapped in test control logic that both manages tier test pre-bond and integrates the tier into the large test architecture post-bond. We describe a new kind of boundary scan to provide the necessary test control and observation of the partial circuits, and we propose a new design methodology for test hardcore that ensures both pre-bond functionality and post-bond optimality. We present the application of these techniques to the 3D-MAPS test vehicle, which has proven their effectiveness. Second, we extend these DFT techniques to circuit-partitioned designs. We find that boundary scan design is generally sufficient, but that some 3D designs require special DFT treatment. Most importantly, we demonstrate that the functional partitioning inherent in 3D design can potentially decrease the total test cost of verifying a circuit. Third, we present a new CAD algorithm for designing 3D test wrappers. This algorithm co-designs the pre-bond and post-bond wrappers to simultaneously minimize test time and routing cost. On average, our algorithm utilizes over 90% of the wires in both the pre-bond and post-bond wrappers. Finally, we look at the 3D vias themselves to develop a low-cost, high-volume pre-bond test methodology appropriate for production-level test. We describe the shorting probes methodology, wherein large test probes are used to contact multiple small 3D vias. This technique is an all-digital test method that integrates seamlessly into existing test flows. Our experimental results demonstrate two key facts: neither the large capacitance of the probe tips nor the process variation in the 3D vias and the probe tips significantly hinders the testability of the circuits. Taken together, this body of work defines a complete test methodology for testing 3D ICs pre-bond, eliminating one of the key hurdles to the commercialization of 3D technology.PhDCommittee Chair: Lee, Hsien-Hsin; Committee Member: Bakir, Muhannad; Committee Member: Lim, Sung Kyu; Committee Member: Vuduc, Richard; Committee Member: Yalamanchili, Sudhaka

Design-for-Test and Test Optimization Techniques for TSV-based 3D Stacked ICs

<p>As integrated circuits (ICs) continue to scale to smaller dimensions, long interconnects</p><p>have become the dominant contributor to circuit delay and a significant component of</p><p>power consumption. In order to reduce the length of these interconnects, 3D integration</p><p>and 3D stacked ICs (3D SICs) are active areas of research in both academia and industry.</p><p>3D SICs not only have the potential to reduce average interconnect length and alleviate</p><p>many of the problems caused by long global interconnects, but they can offer greater design</p><p>flexibility over 2D ICs, significant reductions in power consumption and footprint in</p><p>an era of mobile applications, increased on-chip data bandwidth through delay reduction,</p><p>and improved heterogeneous integration.</p><p>Compared to 2D ICs, the manufacture and test of 3D ICs is significantly more complex.</p><p>Through-silicon vias (TSVs), which constitute the dense vertical interconnects in a</p><p>die stack, are a source of additional and unique defects not seen before in ICs. At the same</p><p>time, testing these TSVs, especially before die stacking, is recognized as a major challenge.</p><p>The testing of a 3D stack is constrained by limited test access, test pin availability,</p><p>power, and thermal constraints. Therefore, efficient and optimized test architectures are</p><p>needed to ensure that pre-bond, partial, and complete stack testing are not prohibitively</p><p>expensive.</p><p>Methods of testing TSVs prior to bonding continue to be a difficult problem due to test</p><p>access and testability issues. Although some built-in self-test (BIST) techniques have been</p><p>proposed, these techniques have numerous drawbacks that render them impractical. In this dissertation, a low-cost test architecture is introduced to enable pre-bond TSV test through</p><p>TSV probing. This has the benefit of not needing large analog test components on the die,</p><p>which is a significant drawback of many BIST architectures. Coupled with an optimization</p><p>method described in this dissertation to create parallel test groups for TSVs, test time for</p><p>pre-bond TSV tests can be significantly reduced. The pre-bond probing methodology is</p><p>expanded upon to allow for pre-bond scan test as well, to enable both pre-bond TSV and</p><p>structural test to bring pre-bond known-good-die (KGD) test under a single test paradigm.</p><p>The addition of boundary registers on functional TSV paths required for pre-bond</p><p>probing results in an increase in delay on inter-die functional paths. This cost of test</p><p>architecture insertion can be a significant drawback, especially considering that one benefit</p><p>of 3D integration is that critical paths can be partitioned between dies to reduce their delay.</p><p>This dissertation derives a retiming flow that is used to recover the additional delay added</p><p>to TSV paths by test cell insertion.</p><p>Reducing the cost of test for 3D-SICs is crucial considering that more tests are necessary</p><p>during 3D-SIC manufacturing. To reduce test cost, the test architecture and test</p><p>scheduling for the stack must be optimized to reduce test time across all necessary test</p><p>insertions. This dissertation examines three paradigms for 3D integration - hard dies, firm</p><p>dies, and soft dies, that give varying degrees of control over 2D test architectures on each</p><p>die while optimizing the 3D test architecture. Integer linear programming models are developed</p><p>to provide an optimal 3D test architecture and test schedule for the dies in the 3D</p><p>stack considering any or all post-bond test insertions. Results show that the ILP models</p><p>outperform other optimization methods across a range of 3D benchmark circuits.</p><p>In summary, this dissertation targets testing and design-for-test (DFT) of 3D SICs.</p><p>The proposed techniques enable pre-bond TSV and structural test while maintaining a</p><p>relatively low test cost. Future work will continue to enable testing of 3D SICs to move</p><p>industry closer to realizing the true potential of 3D integration.</p>Dissertatio

A 3D IC BIST for pre-bond test of TSVs using Ring Oscillators

International audience3D stacked integrated circuits based on Through Silicon Vias (TSV) are promising with their high performances and small form factor. However, these circuits present many test issues, especially for TSVs. In this paper we propose a novel Built-In-Self-Test (BIST) architecture for pre-bond testing of TSVs in 3D stacked integrated circuits. The main idea is to measure the variation of TSVs capacitances in order to detect defective TSVs. The BIST architecture is based on ring oscillators, frequencies of which depend on TSVs capacitances. The proposed BIST is integrated within the JTAG standard. This paper presents spice simulation results and logic synthesis results of the proposed TSV ring oscillator structure using a 65 nm CMOS technology, including 10 μm diameter TSV middle technology. Due to local process variations, the proposed test architecture is limited in accuracy; it detects only large capacitive faults on TSVs

Vernier Ring Based Pre-bond Through Silicon Vias Test in 3D ICs

Defects in TSV will lead to variations in the propagation delay of the net connected to the faulty TSV. A non-invasive Vernier Ring based method for TSV pre-bond testing is proposed to detect resistive open and leakage faults. TSVs are used as capacitive loads of their driving gates, then time interval compared with the fault-free TSVs will be detected. The time interval can be detected with picosecond level resolution, and digitized into a digital code to compare with an expected value of fault-free. Experiments on fault detection are presented through HSPICE simulations using realistic models for a 45 nm CMOS technology. The results show the effectiveness in the detection of time interval 10 ps, resistive open defects 0.2 kΩ above and equivalent leakage resistance less than 18 MΩ. Compared with existing methods, detection precision, area overhead, and test time are effectively improved, furthermore, the fault degree can be digitalized into digital code

Thermal-Aware Test Schedule and TAM Co-Optimization for Three-Dimensional IC

[[abstract]]Testing is regarded as one of the most difficult challenges for three-dimensional integrated circuits (3D ICs). In this paper, we want to optimize the cost of TAM (test access mechanism) and the test time for 3D IC. We used both greedy and simulated annealing algorithms to solve this optimization problem. We compare the results of two assumptions: soft-die mode and hard-die mode. The former assumes that the DfT of dies cannot be changed, while the latter assumes that the DfT of dies can be adjusted. The results show that thermal-aware cooptimization is essential to decide the optimal TAM and test schedule. Blindly adding TAM cannot reduce the total test cost due to temperature constraints. Another conclusion is that soft-die mode is more effective than hard-die mode to reduce the total test cost for 3D IC.[[notice]]補正完畢[[booktype]]電子

Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions

Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fast and accurate predictions of atomistic chemical properties, they do not explicitly capture the electronic degrees of freedom of a molecule, which limits their applicability for reactive chemistry and chemical analysis. Here we present a deep learning framework for the prediction of the quantum mechanical wavefunction in a local basis of atomic orbitals from which all other ground-state properties can be derived. This approach retains full access to the electronic structure via the wavefunction at force-field-like efficiency and captures quantum mechanics in an analytically differentiable representation. On several examples, we demonstrate that this opens promising avenues to perform inverse design of molecular structures for target electronic property optimisation and a clear path towards increased synergy of machine learning and quantum chemistry