Date: Wednesday 29 March 2017
Time: 08:30 - 10:00
Location / Room: 4BC
Chair:
Jim Harkin, Ulster University, GB
This session presents recent advances in emerging computing strategies including Reversible Computing and Stochastic Computing with improvements in energy efficiency and reductions in computational complexity. An acceleration platform for the design exploration of Quantum Computers is also presented.
| Time | Label | Presentation Title Authors |
|---|---|---|
| 08:30 | 5.2.1 | MAKE IT REVERSIBLE: EFFICIENT EMBEDDING OF NON-REVERSIBLE FUNCTIONS Speaker: Alwin Zulehner, Johannes Kepler University, Linz, AT Authors: Alwin Zulehner1 and Robert Wille2 1Johannes Kepler University, AT; 2Johannes Kepler University Linz, AT Abstract Reversible computation became established as a promising concept due to its application in various areas like quantum computation, energy-aware circuits, and further areas. Unfortunately, most functions of interest are non-reversible. Therefore, a process called embedding has to be conducted to transform a non-reversible function into a reversible one - a coNP-hard problem. Existing solutions suffer from the resulting exponential complexity and, hence, are limited to rather small functions only. In this work, an approach is presented which tackles the problem in an entirely new fashion. We divide the embedding process into matrix operations, which can be conducted efficiently on a certain kind of decision diagram. Experiments show that improvements of several orders of magnitudes can be achieved using the proposed method. Moreover, for many benchmarks exact results can be obtained for the first time ever. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 09:00 | 5.2.2 | QX: A HIGH-PERFORMANCE QUANTUM COMPUTER SIMULATION PLATFORM Speaker: Nader Khammassi, QuTech, Computer Engineering Lab, Delft University of Technology, NL Authors: Nader Khammassi, Imran Ashraf, Xiang Fu, Carmina Garcia Almudever and Koen Bertels, QuTech, Computer Engineering Lab, Delft University of Technology, NL Abstract Quantum computing is rapidly evolving especially after the discovery of several efficient quantum algorithms solving intractable classical problems such as Shor's factoring algorithm. However the realization of a large-scale physical quantum computer is very challenging and the number of qubits that are currently under development is still very low, namely less than 15. In the absence of large size platforms, quantum computer simulation is critical for developing and testing quantum algorithms and investigating the different challenges facing the design of quantum computer hardware. What makes quantum computer simulation on classical computers particularly challenging are the memory and computational resource requirements. In this paper, we introduce a universal quantum computer simulator, called QX, that takes as input a specially designed quantum assembly language, called QASM, and provides, through agressive optimisations, high simulation speeds and large number of qubits. QX allows the simulation of up to 34 fully entangled qubits on a single node using less than 270 GB of memory. Our experiments using different quantum algorithms show that QX achieves significant simulation speedup over similar state-of-the-art simulation environment. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 09:30 | 5.2.3 | DESIGN AUTOMATION AND DESIGN SPACE EXPLORATION FOR QUANTUM COMPUTERS Speaker: Mathias Soeken, EPFL, CH Authors: Mathias Soeken1, Martin Roetteler2, Nathan Wiebe2 and Giovanni De Micheli1 1EPFL, CH; 2Microsoft Research, US Abstract A major hurdle to the deployment of quantum linear systems algorithms and recent quantum simulation algorithms lies in the difficulty to find inexpensive reversible circuits for arithmetic using existing hand coded methods. Motivated by recent advances in reversible logic synthesis, we synthesize arithmetic circuits using classical design automation flows and tools. The combination of classical and reversible logic synthesis enables the automatic design of large components in reversible logic starting from well-known hardware description languages such as Verilog. As a prototype example for our approach we automatically generate high quality networks for the reciprocal 1/x, which is necessary for quantum linear systems algorithms. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 10:00 | IP2-13, 464 | ENERGY EFFICIENT STOCHASTIC COMPUTING WITH SOBOL SEQUENCES Speaker: Siting Liu, University of Alberta, CA Authors: Siting Liu and Jie Han, University of Alberta, CA Abstract Energy efficiency presents a significant challenge for stochastic computing (SC) due to the long random binary bit streams required for accurate computation. In this paper, a type of low discrepancy (LD) sequences, the Sobol sequence, is considered for energy-efficient implementations of SC circuits. The use of Sobol sequences improves the output accuracy of a stochastic circuit with a reduced sequence length compared to the use of another type of LD sequences, the Halton sequence, and conventional LFSR-generated pseudorandom sequences. The use of Sobol sequences leads to a similar or higher accuracy than using Halton sequences for basic arithmetic operations. Sobol sequence generators cost less energy than the Halton counterparts when multiple random sequences are required in a circuit, thus the use of Sobol sequences can lead to a higher energy efficiency in an SC circuit than using Halton sequences. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 10:01 | IP2-14, 308 | LOGIC ANALYSIS AND VERIFICATION OF N-INPUT GENETIC LOGIC CIRCUITS Speaker: Hasan Baig, Technical University of Denmark, DK Authors: Hasan Baig and Jan Madsen, Technical University of Denmark, DK Abstract Nature is using genetic logic circuits to regulate the fundamental processes of life. These genetic logic circuits are triggered by a combination of external signals, such as chemicals, proteins, light and temperature, to emit signals to control other gene expressions or metabolic pathways accordingly. As compared to electronic circuits, genetic circuits exhibit stochastic behavior and do not always behave as intended. Therefore, there is a growing interest in being able to analyze and verify the logical behavior of a genetic circuit model, prior to its physical implementation in a laboratory. In this paper, we present an approach to analyze and verify the Boolean logic of a genetic circuit from the data obtained through stochastic analog circuit simulations. The usefulness of this analysis is demonstrated through different case studies illustrating how our approach can be used to verify the expected behavior of an n-input genetic logic circuit. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 10:00 | End of session Coffee Break in Exhibition Area On all conference days (Tuesday to Thursday), coffee and tea will be served during the coffee breaks at the below-mentioned times in the exhibition area. Tuesday, March 28, 2017
Wednesday, March 29, 2017
Thursday, March 30, 2017
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