Publications

Nash equilibria in the two-player kidney exchange game

Margarida Carvalho

Andrea Lodi

João Pedro Pedroso

Ana Luiza D'ávila Viana

2016-04-21

Mathematical Programming (publié)

doi.org

Fault-Tolerant Associative Memories Based on $c$-Partite Graphs

François Leduc-Primeau

Vincent Gripon

Michael Rabbat

Warren Gross

Associative memories allow the retrieval of previously stored messages given a part of their content. In this paper, we are interested in as… (voir plus)sociative memories based on c-partite graphs that were recently introduced. These memories are almost optimal in terms of the amount of storage they require (efficiency) and allow retrieving messages with low complexity. We propose a generic implementation model for the retrieval algorithm that can be readily mapped to an integrated circuit and study the retrieval performance when hardware components are affected by faults. We show using analytical and simulation results that these associative memories can be made resilient to circuit faults with a minor modification of the retrieval algorithm. In one example, the memory retains 88% of its efficiency when 1% of the storage cells are faulty, or 98% when 0.1% of the binary outputs of the retrieval algorithm are faulty. When considering storage faults, the fault tolerance exhibited by the proposed associative memory can be comparable to using a capacity-achieving error correction code for protecting the stored information.

2016-02-15

IEEE Transactions on Signal Processing (publié)

doi.org

Fault-Tolerant Associative Memories Based on $c$-Partite Graphs

François Leduc-Primeau

Vincent Gripon

Michael Rabbat

Warren Gross

Associative memories allow the retrieval of previously stored messages given a part of their content. In this paper, we are interested in as… (voir plus)sociative memories based on c-partite graphs that were recently introduced. These memories are almost optimal in terms of the amount of storage they require (efficiency) and allow retrieving messages with low complexity. We propose a generic implementation model for the retrieval algorithm that can be readily mapped to an integrated circuit and study the retrieval performance when hardware components are affected by faults. We show using analytical and simulation results that these associative memories can be made resilient to circuit faults with a minor modification of the retrieval algorithm. In one example, the memory retains 88% of its efficiency when 1% of the storage cells are faulty, or 98% when 0.1% of the binary outputs of the retrieval algorithm are faulty. When considering storage faults, the fault tolerance exhibited by the proposed associative memory can be comparable to using a capacity-achieving error correction code for protecting the stored information.

2016-02-01

IEEE Transactions on Signal Processing (publié)

doi.org

Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging

Henning Müller

B. Kelm

Tal Arbel

Weidong (Tom) Cai

M. Jorge Cardoso

Georg Langs

Bjoern Menze

Dimitris N. Metaxas

Albert A. Montillo

William Wells

Shaoting Zhang

Albert C.S. Chung

M. Jenkinson

Annemie Ribbens

2016-01-01

Lecture Notes in Computer Science (publié)

doi.org

Poisson Group Testing: A Probabilistic Model for Boolean Compressed Sensing

Amin Emad

Olgica Milenkovic

We introduce a novel probabilistic group testing framework, termed Poisson group testing, in which the number of defectives follows a right-… (voir plus)truncated Poisson distribution. The Poisson model has a number of new applications, including dynamic testing with diminishing relative rates of defectives. We consider both nonadaptive and semi-adaptive identification methods. For nonadaptive methods, we derive a lower bound on the number of tests required to identify the defectives with a probability of error that asymptotically converges to zero; in addition, we propose test matrix constructions for which the number of tests closely matches the lower bound. For semiadaptive methods, we describe a lower bound on the expected number of tests required to identify the defectives with zero error probability. In addition, we propose a stage-wise reconstruction algorithm for which the expected number of tests is only a constant factor away from the lower bound. The methods rely only on an estimate of the average number of defectives, rather than on the individual probabilities of subjects being defective.

2015-08-15

IEEE Transactions on Signal Processing (publié)

doi.org

arxiv.org

Clinical Image-Based Procedures. Translational Research in Medical Imaging

Ian J. Gerard

Marta Kersten-Oertel

Simon Drouin

Jeffery Alan Hall

Kevin Petrecca

Dante De Nigris

Tal Arbel

D. Collins

2015-01-01

Lecture Notes in Computer Science (publié)

doi.org

Poisson Group Testing: A Probabilistic Model for Boolean Compressed Sensing

Amin Emad

Olgica Milenkovic

We introduce a novel probabilistic group testing framework, termed Poisson group testing, in which the number of defectives follows a right-… (voir plus)truncated Poisson distribution. The Poisson model has a number of new applications, including dynamic testing with diminishing relative rates of defectives. We consider both nonadaptive and semi-adaptive identification methods. For nonadaptive methods, we derive a lower bound on the number of tests required to identify the defectives with a probability of error that asymptotically converges to zero; in addition, we propose test matrix constructions for which the number of tests closely matches the lower bound. For semiadaptive methods, we describe a lower bound on the expected number of tests required to identify the defectives with zero error probability. In addition, we propose a stage-wise reconstruction algorithm for which the expected number of tests is only a constant factor away from the lower bound. The methods rely only on an estimate of the average number of defectives, rather than on the individual probabilities of subjects being defective.

2014-10-20

ArXiv (prépublication)

doi.org

arxiv.org

A Scalable Successive-Cancellation Decoder for Polar Codes

Alexandre J. Raymond

Warren Gross

Polar codes are the first error-correcting codes to provably achieve channel capacity, asymptotically in code length, with an explicit const… (voir plus)ruction. However, under successive-cancellation decoding, polar codes require very long code lengths to compete with existing modern codes. Nonetheless, the successive cancellation algorithm enables very-low-complexity implementations in hardware, due to the regular structure exhibited by polar codes. In this paper, we present an improved architecture for successive-cancellation decoding of polar codes, making use of a novel semi-parallel, encoder-based partial-sum computation module. We also provide quantization results for realistic code length N=215, and explore various optimization techniques such as a chained processing element and a variable quantization scheme. This design is shown to scale to code lengths of up to N=221, enabled by its low logic use, low register use and simple datapaths, limited almost exclusively by the amount of available SRAM. It also supports an overlapped loading of frames, allowing full-throughput decoding with a single set of input buffers.

2014-10-15

IEEE Transactions on Signal Processing (publié)

doi.org

arxiv.org

High-Throughput Energy-Efficient LDPC Decoders Using Differential Binary Message Passing

Kevin Cushon

Saied Hemati

Camille Leroux

Shie Mannor

Warren Gross

In this paper, we present energy-efficient architectures for decoders of low-density parity check (LDPC) codes using the differential decodi… (voir plus)ng with binary message passing (DD-BMP) algorithm and its modified variant (MDD-BMP). We also propose an improved differential binary (IDB) decoding algorithm. These algorithms offer significant intrinsic advantages in the energy domain: simple computations, low interconnect complexity, and very high throughput, while achieving error correction performance up to within 0.25 dB of the offset min-sum algorithm. We report on fully parallel decoder implementations of (273, 191), (1023, 781), and (4095, 3367) finite geometry-based LDPC codes in 65 nm CMOS. Using the MDD-BMP algorithm, these decoders achieve respective areas of 0.28 mm2, 1.38 mm2, and 15.37 mm2, average throughputs of 37 Gbps, 75 Gbps, and 141 Gbps, and energy efficiencies of 4.9 pJ/bit, 13.2 pJ/bit, and 37.9 pJ/bit with a 1.0 V supply voltage in post-layout simulations. At a reduced supply voltage of 0.8 V, these decoders achieve respective throughputs of 26 Gbps, 54 Gbps, and 94 Gbps, and energy efficiencies of 3.1 pJ/bit, 8.2 pJ/bit, and 23.5 pJ/bit. We also report on a fully parallel implementation of IDB for the (2048, 1723) LDPC code specified in the IEEE 802.3an (10GBASE-T) standard. This decoder achieves an area of 1.44 mm2, average throughput of 172 Gbps, and an energy efficiency of 2.8 pJ/bit with a 1.0 V supply voltage; at 0.8 V, it achieves throughput of 116 Gbps and energy efficiency of 1.7 pJ/bit.

2014-02-01

IEEE Transactions on Signal Processing (publié)

doi.org

High-Throughput Energy-Efficient LDPC Decoders Using Differential Binary Message Passing

Kevin Cushon

Saied Hemati

Camille Leroux

Shie Mannor

Warren Gross

In this paper, we present energy-efficient architectures for decoders of low-density parity check (LDPC) codes using the differential decodi… (voir plus)ng with binary message passing (DD-BMP) algorithm and its modified variant (MDD-BMP). We also propose an improved differential binary (IDB) decoding algorithm. These algorithms offer significant intrinsic advantages in the energy domain: simple computations, low interconnect complexity, and very high throughput, while achieving error correction performance up to within 0.25 dB of the offset min-sum algorithm. We report on fully parallel decoder implementations of (273, 191), (1023, 781), and (4095, 3367) finite geometry-based LDPC codes in 65 nm CMOS. Using the MDD-BMP algorithm, these decoders achieve respective areas of 0.28 mm2, 1.38 mm2, and 15.37 mm2, average throughputs of 37 Gbps, 75 Gbps, and 141 Gbps, and energy efficiencies of 4.9 pJ/bit, 13.2 pJ/bit, and 37.9 pJ/bit with a 1.0 V supply voltage in post-layout simulations. At a reduced supply voltage of 0.8 V, these decoders achieve respective throughputs of 26 Gbps, 54 Gbps, and 94 Gbps, and energy efficiencies of 3.1 pJ/bit, 8.2 pJ/bit, and 23.5 pJ/bit. We also report on a fully parallel implementation of IDB for the (2048, 1723) LDPC code specified in the IEEE 802.3an (10GBASE-T) standard. This decoder achieves an area of 1.44 mm2, average throughput of 172 Gbps, and an energy efficiency of 2.8 pJ/bit with a 1.0 V supply voltage; at 0.8 V, it achieves throughput of 116 Gbps and energy efficiency of 1.7 pJ/bit.

2014-02-01

IEEE Transactions on Signal Processing (publié)

doi.org

Bayesian and grAphical Models for Biomedical Imaging

M. Cardoso

Ivor J. A. Simpson

Tal Arbel

Doina Precup

Annemie Ribbens

2014-01-01

Lecture Notes in Computer Science (publié)

doi.org