No Arabic abstract
The CMOS integrated chips at advanced technology nodes are becoming more vulnerable to various sources of faults like manufacturing imprecisions, variations, aging, etc. Additionally, the intentional fault attacks (e.g., high power microwave, cybersecurity threats, etc.) and environmental effects (i.e., radiation) also pose reliability threats to integrated circuits. Though the traditional hardware redundancy-based techniques like Triple Modular Redundancy (TMR), Quadded (QL) Logic etc. mitigate the risk to some extent, they add huge hardware overhead and are not very effective. Truly polymorphic circuits that are inherently capable of achieving multiple functionalities in a limited footprint could enhance the faultresilience/recovery of the circuits with limited overhead. We demonstrate a novel crosstalk logic based polymorphic circuit approach to achieve compact and efficient fault resilient circuits. We show a range of polymorphic primitive gates and their usage in a functional unit. The functional unit is a single arithmetic circuit that is capable of delivering Multiplication/Sorting/Addition output depending on the control inputs. Using such polymorphic computing units in an ALU would imply that a correct path for functional output is possible even when 2/3rd of the ALU is damaged. Our comparison results with respect to existing polymorphic techniques and CMOS reveal 28% and 62% reduction in transistor count respectively for the same functionalities. In conjunction with fault detection algorithms, the proposed polymorphic circuit concept can be transformative for fault tolerant circuit design directions with minimum overhead.
Micro- and nanosatellites have become popular platforms for a variety of commercial and scientific applications, but today are considered suitable mainly for short and low-priority space missions due to their low reliability. In part, this can be attributed to their reliance upon cheap, low-feature size, COTS components originally designed for embedded and mobile-market applications, for which traditional hardware-voting concepts are ineffective. Software-fault-tolerance concepts have been shown effective for such systems, but have largely been ignored by the space industry due to low maturity, as most have only been researched in theory. In practice, designers of payload instruments and miniaturized satellites are usually forced to sacrifice reliability in favor deliver the level of performance necessary for cutting-edge science and innovative commercial applications. Thus, we developed a software-fault-tolerance-approach based upon thread-level coarse-grain lockstep, which was validated using fault-injection. To offer strong long-term fault coverage, our architecture is implemented as tiled MPSoC on an FPGA, utilizing partial reconfiguration, as well as mixed criticality. This architecture can satisfy the high performance requirements of current and future scientific and commercial space missions at very low cost, while offering the strong fault-coverage guarantees necessary for platform control even for missions with a long duration. This architecture was developed for a 4-year ESA project. Together with two industrial partners, we are developing a prototype to then undergo radiation testing.
Quantum computation promises significant computational advantages over classical computation for some problems. However, quantum hardware suffers from much higher error rates than in classical hardware. As a result, extensive quantum error correction is required to execute a useful quantum algorithm. The decoder is a key component of the error correction scheme whose role is to identify errors faster than they accumulate in the quantum computer and that must be implemented with minimum hardware resources in order to scale to the regime of practical applications. In this work, we consider surface code error correction, which is the most popular family of error correcting codes for quantum computing, and we design a decoder micro-architecture for the Union-Find decoding algorithm. We propose a three-stage fully pipelined hardware implementation of the decoder that significantly speeds up the decoder. Then, we optimize the amount of decoding hardware required to perform error correction simultaneously over all the logical qubits of the quantum computer. By sharing resources between logical qubits, we obtain a 67% reduction of the number of hardware units and the memory capacity is reduced by 70%. Moreover, we reduce the bandwidth required for the decoding process by a factor at least 30x using low-overhead compression algorithms. Finally, we provide numerical evidence that our optimized micro-architecture can be executed fast enough to correct errors in a quantum computer.
Considering the large-scale quantum computer, it is important to know how much quantum computational resources is necessary precisely and quickly. Unfortunately the previous methods so far cannot support a large-scale quantum computing practically and therefore the analysis because they usually use a non-structured code. To overcome this problem, we propose a fast mapping by using the hierarchical assembly code which is much more compact than the non-structured code. During the mapping process, the necessary modules and their interconnection can be dynamically mapped by using the communication bus at the cost of additional qubits. In our study, the proposed method works very fast such as 1 hour than 1500 days for Shor algorithm to factorize 512-bit integer. Meanwhile, since the hierarchical assembly code has high degree of locality, it has shorter SWAP chains and hence it does not increase the quantum computation time than expected.
Quantum error correction (QEC) is an essential step towards realising scalable quantum computers. Theoretically, it is possible to achieve arbitrarily long protection of quantum information from corruption due to decoherence or imperfect controls, so long as the error rate is below a threshold value. The two-dimensional surface code (SC) is a fault-tolerant error correction protocol} that has garnered considerable attention for actual physical implementations, due to relatively high error thresholds ~1%, and restriction to planar lattices with nearest-neighbour interactions. Here we show a necessary element for SC error correction: high-fidelity parity detection of two code qubits via measurement of a third syndrome qubit. The experiment is performed on a sub-section of the SC lattice with three superconducting transmon qubits, in which two independent outer code qubits are joined to a central syndrome qubit via two linking bus resonators. With all-microwave high-fidelity single- and two-qubit nearest-neighbour entangling gates, we demonstrate entanglement distributed across the entire sub-section by generating a three-qubit Greenberger-Horne-Zeilinger (GHZ) state with fidelity ~94%. Then, via high-fidelity measurement of the syndrome qubit, we deterministically entangle the otherwise un-coupled outer code qubits, in either an even or odd parity Bell state, conditioned on the syndrome state. Finally, to fully characterize this parity readout, we develop a new measurement tomography protocol to obtain a fidelity metric (90% and 91%). Our results reveal a straightforward path for expanding superconducting circuits towards larger networks for the SC and eventually a primitive logical qubit implementation.
A long-standing open question about Gaussian continuous-variable cluster states is whether they enable fault-tolerant measurement-based quantum computation. The answer is yes. Initial squeezing in the cluster above a threshold value of 20.5 dB ensures that errors from finite squeezing acting on encoded qubits are below the fault-tolerance threshold of known qubit-based error-correcting codes. By concatenating with one of these codes and using ancilla-based error correction, fault-tolerant measurement-based quantum computation of theoretically indefinite length is possible with finitely squeezed cluster states.