Guy-Armand Kamendje

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This paper proposes majority-based tracking forecast memories (MTFMs) for area efficient high throughput ASIC implementation of stochastic Low-Density Parity-Check (LDPC) decoders. The proposed method is applied for ASIC implementation of a fully parallel stochastic decoder that decodes the (2048, 1723) LDPC code from the IEEE 802.3an (10GBASE-T) standard.(More)
The performance of elliptic curve (EC) cryptosystems depends essentially on efficient arithmetic in the underlying finite field. Binary finite fields GF(2m) have the advantage of “carry-free” addition. Multiplication, on the other hand, is rather costly since polynomial arithmetic is not supported by general-purpose processors. In this paper we propose a(More)
This paper proposes Tracking Forecast Memories (TFMs) as a novel method for implementing re-randomization and decorrelation of stochastic bit streams in stochastic channel decoders. We show that TFMs are able to achieve decoding performance similar to that of the previous methods in the literature (i.e., edge memories or EMs), but they exhibit much lower(More)
Montgomery multiplication normally spends over 90% of its execution time in inner loops executing some kind of multiply-and-add operations. The performance of these critical code sections can be greatly improved by customizing the processor’s instruction set for low-level arithmetic functions. In this paper, we investigate the potential of architectural(More)
Recent multi-application smart cards are equipped with powerful 32-bit RISC cores clocked at 33 MHz or even more. They are able to support a variety of public-key cryptosystems, including elliptic curve systems over prime fields GF(p) and binary fields GF(2) of arbitrary order. This flexibility is achieved by implementing the cryptographic primitives in(More)
We present an architecture for digit-serial multiplication in finite fields GF(2m) with applications to cryptography. The proposed design uses polynomial basis representation and interleaves multiplication steps with degree reduction steps. An M-bit multiplier works with arbitrary irreducible polynomials and can be used for any binary field of order 2m ≤ 2M(More)
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