IEEE transactions on very large scale integration (VLSI) systems

There is a growing concern about the increasing vulnerability of future computing systems to errors in the underlying hardware. Traditional redundancy techniques are expensive for designing energy-efficient systems that are resilient to high error rates. We present Error Resilient System Architecture (ERSA), a low-cost robust system architecture for emerging killer probabilistic applications such as Recognition, Mining and Synthesis (RMS) applications. While resilience of such applications to errors in low-order bits of data is well-known, execution of such applications on error-prone hardware significantly degrades output quality (due to high-order bit errors and crashes). ERSA achieves high error resilience to high-order bit errors and control errors (in addition to low-order bit errors) using a judicious combination of 3 key ideas: (1) asymmetric reliability in many-core architectures, (2) error-resilient algorithms at the core of probabilistic applications, and (3) intelligent software optimizations. Error injection experiments on a multi-core ERSA hardware prototype demonstrate that, even at very high error rates of 20,000 errors/second/core or 2×10−4 error/cycle/core (with errors injected in architecturally-visible registers), ERSA maintains 90% or better accuracy of output results, together with minimal impact on execution time, for probabilistic applications such as K-Means clustering, LDPC decoding and Bayesian networks. Moreover, we demonstrate the effectiveness of ERSA in tolerating high rates of static memory errors that are characteristic of emerging challenges such as Vccmin problems and erratic bit errors. Using the concept of configurable reliability, ERSA platforms may also be adapted for general-purpose applications that are less resilient to errors (but at higher costs).

ERSA: error resilient system architecture for probabilistic applications

A method and system for decoding low density parity check (“LDPC”) codes. An LDPC decoder includes an R select unit, a Q message first-in first-out (“FIFO”) memory, and a cyclic shifter. The R select unit provides an R message by selecting from a plurality of possible R message values. The Q message memory stores a Q message until an R message is generated by a CNU, the Q message and the R message are combined to provide a P message. The cyclic shifter shifts the P message.

Low density parity check decoder for regular LDPC codes

There is a growing concern about the increasing vulnerability of future computing systems to errors in the underlying hardware. Traditional redundancy techniques are expensive for designing energy-efficient systems that are resilient to high error rates. We present Error Resilient System Architecture (ERSA), a robust system architecture which targets emerging killer applications such as recognition, mining, and synthesis (RMS) with inherent error resilience, and ensures high degrees of resilience at low cost. Using the concept of configurable reliability, ERSA may also be adapted for general-purpose applications that are less resilient to errors (but at higher costs). While resilience of RMS applications to errors in low-order bits of data is well-known, execution of such applications on error-prone hardware significantly degrades output quality (due to high-order bit errors and crashes). ERSA achieves high error resilience to high-order bit errors and control flow errors (in addition to low-order bit errors) using a judicious combination of the following key ideas: 1) asymmetric reliability in many-core architectures; 2) error-resilient algorithms at the core of probabilistic applications; and 3) intelligent software optimizations. Error injection experiments on a multicore ERSA hardware prototype demonstrate that, even at very high error rates of 20 errors/flip-flop/108 cycles (equivalent to 25000 errors/core/s), ERSA maintains 90% or better accuracy of output results, together with minimal impact on execution time, for probabilistic applications such as K-Means clustering, LDPC decoding, and Bayesian network inference. In addition, we demonstrate the effectiveness of ERSA in tolerating high rates of static memory errors that are characteristic of emerging challenges related to SRAM Vccmin problems and erratic bit errors.

ERSA: Error Resilient System Architecture for Probabilistic Applications

Reliability concerns due to technology scaling have been a major focus of researchers and designers for several technology nodes. Therefore, many new techniques for enhancing and optimizing reliability have emerged particularly within the last five to ten years. This perspective paper introduces the most prominent reliability concerns from today's points of view and roughly recapitulates the progress in the community so far. The focus of this paper is on perspective trends from the industrial as well as academic points of view that suggest a way for coping with reliability challenges in upcoming technology nodes.

Reliable on-chip systems in the nano-era: lessons learnt and future trends

The upcoming IEEE WiMax 802.16e standard, also referred to as WirelessMAN (2005), is the next step toward very high throughput wireless backbone architectures, supporting up to 500 Mbps. It features as an advanced channel coding scheme low-density parity-check codes. The decoding of LDPC codes is an iterative process, hence many data have to be exchanged between processing units within each iteration. The variety of the specified codes and the envision of different decoding schedules for different codes pose significant challenges to an LDPC decoder hardware realization. In this paper, we present to the best of our knowledge the first published LDPC decoder architecture capable to process all specified WiMax LDPC codes. Detailed synthesis and communications performance results are shown in addition

A Synthesizable IP Core for WIMAX 802.16E LDPC Code Decoding

This paper presents the design of low complexity LDPC codes decoders for the upcoming WiFi (IEEE 802.11n), WiMax (IEEE802.16e) and DVB-S2 standards. A complete exploration of the design space spanning from the decoding schedules, the node processing approximations up to the top-level decoder architecture is detailed. According to this search state-of-the-art techniques for a low complexity design have been adopted in order to meet feasible high throughput decoder implementations. An analysis of the standardized codes from the decoder-aware point of view is also given, presenting, for each one, the implementation challenges (multi rates-length codes) and bottlenecks related to the complete coverage of the standards. Synthesis results on a present 65nm CMOS technology are provided on a generic decoder architecture.

/pdf/low-complexity-ldpc-code-decoders-for-next-generation-4e4bx3i62w.pdf

Low complexity LDPC code decoders for next generation standards

In modern communication systems the required data rates are continuously increasing. High speed transmissions can easily generate throughputs far beyond 1 Tbit/s. To ensure error free communication, channel codes like Low-Density Parity Check (LDPC) codes are utilized. However state-of-the-art LDPC decoders can process only data rates in the range of 10 to 50 Gbit/s. This results in a gap in decoder performance which has to be closed. Therefore we propose a new ultra high speed LDPC decoder architecture. We show that our architecture significantly reduces the routing congestion which poses a big problem for fully parallel, high speed LDPC decoders. The presented 65nm ASIC implementation runs at 257 MHz and consumes an area of 12 mm2The resulting system throughput is 160 Gbit/s, it is the fastest LDPC decoder which has been published up to now. At the same time we show that extremely parallel architectures do not only increase the maximum throughput but also increase area and power efficiency in comparison to state-of-the-art decoders.

A new dimension of parallelism in ultra high throughput LDPC decoding

Future mobile and wireless communication networks require flexible modem architectures to provide seamless services between different network standards. In this paper we focus on the outer modem which has to support various advanced channel coding techniques like convolutional codes, turbo codes, and low-density parity-check (LDPC) codes. We present an application-specific instruction-set processor (ASIP) which supports convolutional codes, binary/duo-binary turbo codes, and LDPC codes. Special emphasis is put on the support of LDPC codes. The ASIP consists of a special pipeline which is completely optimized for channel decoding. Logic synthesis yields an overall area of 0.62 mm2 for this ASIP in a 65 nm low power technology. Payload throughputs of, e.g., up to 257 Mbps are possible at 400 MHz for the WiMAX and WiFi LDPC codes, outperforming existing ASIP solutions for LDPC decoding by an order of magnitude.

/pdf/flexichap-a-reconfigurable-asip-for-convolutional-turbo-and-3nhcv3o440.pdf

FlexiChaP: A reconfigurable ASIP for convolutional, turbo, and LDPC code decoding

In this paper a programmable Forward Error Correction (FEC) IP for a DVB-S2 receiver is presented. It is composed of a Low-Density Parity Check (LDPC), a Bose-Chaudhuri-Hoquenghem (BCH) decoder, and pre- and postprocessing units. Special emphasis is put on LDPC decoding, since it accounts for the most complexity of the IP core by far.We propose a highly efficient LDPC decoder which applies Gauss-Seidel decoding. In contrast to previous publications, we show in detail how to solve the well known problem of superpositions of permutation matrices. The enhanced convergence speed of Gauss-Seidel decoding is used to reduce area and power consumption. Furthermore, we propose a modified version of the λ-Min algorithm which allows to further decrease the memory requirements of the decoder by compressing the extrinsic information.Compared to the latest published DVB-S2 LDPC decoders, we could reduce the clock frequency by 40% and the memory consumption by 16%, yielding large energy and area savings while offering the same throughput.

Matthias Alles

Papers

A Synthesizable IP Core for WIMAX 802.16E LDPC Code Decoding

Low complexity LDPC code decoders for next generation standards

A new dimension of parallelism in ultra high throughput LDPC decoding

FlexiChaP: A reconfigurable ASIP for convolutional, turbo, and LDPC code decoding

A novel LDPC decoder for DVB-S2 IP