- Award ID(s):
- 1717602
- PAR ID:
- 10191402
- Date Published:
- Journal Name:
- IEEE International Symposium on Information Theory (ISIT 2020)
- Page Range / eLocation ID:
- 688 to 693
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
In data storage and data transmission, certain patterns are more likely to be subject to error when written (transmitted) onto the media. In magnetic recording systems with binary data and bipolar non-return-to-zero signaling, patterns that have insufficient separation between consecutive transitions exacerbate inter-symbol interference. Constrained codes are used to eliminate such error-prone patterns. A recent example is a new family of capacity-achieving constrained codes, named lexicographically-ordered constrained codes (LOCO codes). LOCO codes are symmetric, that is, the set of forbidden patterns is closed under taking pattern complements. LOCO codes are suboptimal in terms of rate when used in Flash devices where block erasure is employed since the complement of an error-prone pattern is not detrimental in these devices. This paper introduces asymmetric LOCO codes (A-LOCO codes), which are lexicographically-ordered constrained codes that forbid only those patterns that are detrimental for Flash performance. A-LOCO codes are also capacity-achieving, and at finite-lengths, they offer higher rates than the available state-of-the-art constrained codes designed for the same goal. The mapping-demapping between the index and the codeword in A-LOCO codes allows low-complexity encoding and decoding algorithms that are simpler than their LOCO counterparts.more » « less
-
In order to meet the demands of data-hungry applications, data storage devices are required to be increasingly denser. Various sources of error appear with this increase in density. Multi-dimensional (MD) graph-based codes are capable of mitigating error sources like interference and channel non-uniformity in dense storage devices. Recently, a technique was proposed to enhance the performance of MD spatially-coupled codes that are based on circulants. The technique carefully relocates circulants to minimize the number of short cycles. However, cycles become more detrimental when they combine together to form more advanced objects, e.g., absorbing sets, including low-weight codewords. In this paper, we show how MD relocations can be exploited to minimize the number of detrimental objects in the graph of an MD code. Moreover, we demonstrate the savings in the number of relocation arrangements earned by focusing on objects rather than cycles. Our technique is applicable to a wide variety of one-dimensional (OD) codes. Simulation results reveal significant lifetime gains in practical Flash systems achieved by MD codes designed using our technique compared with OD codes having similar parameters.more » « less
-
We present the Hybrid Polar Decoder (HyPD), a hybrid classical-quantum decoder design for Polar error correction codes, which are becoming widespread in today’s 5G and tomorrow’s 6G networks. HyPD employs CMOS processing for the Polar decoder’s binary tree traversal, and Quantum Annealing (QA) processing for the Quantum Polar Decoder (QPD)-a Maximum-Likelihood QA-based Polar decoder submodule. QPD’s design efficiently transforms a Polar decoder into a quadratic polynomial optimization form, then maps this polynomial on to the physical QA hardware via QPD-MAP, a customized problem mapping scheme tailored to QPD. We have experimentally evaluated HyPD on a state-of-the-art QA device with 5,627 qubits, for 5G-NR Polar codes with block length of 1,024 bits, in Rayleigh fading channels. Our results show that HyPD outperforms Successive Cancellation List decoders of list size eight by half an order of bit error rate magnitude, and achieves a 1,500-bytes frame delivery rate of 99.1%, at 1 dB signal-to-noise ratio. Further studies present QA compute time considerations. We also propose QPD-HW, a novel QA hardware topology tailored for the task of decoding Polar codes. QPD-HW is sparse, flexible to code rate and block length, and may be of potential interest to the designers of tomorrow’s 6G wireless networks.more » « less
-
Compression and efficient storage of
neural network (NN) parameters is critical for applications that run on resource-constrained devices. Despite the significant progress in NN model compression, there has been considerably less investigation in the actualphysical storage of NN parameters. Conventionally, model compression and physical storage are decoupled, as digital storage media witherror-correcting codes (ECCs) provide robust error-free storage. However, this decoupled approach is inefficient as it ignores the overparameterization present in most NNs and forces the memory device to allocate the same amount of resources to every bit of information regardless of its importance. In this work, we investigate analog memory devices as an alternative to digital media – one that naturally provides a way to add more protection for significant bits unlike its counterpart, but is noisy and may compromise the stored model’s performance if used naively. We develop a variety of robust coding strategies for NN weight storage on analog devices, and propose an approach to jointly optimize model compression and memory resource allocation. We then demonstrate the efficacy of our approach on models trained on MNIST, CIFAR-10, and ImageNet datasets for existing compression techniques. Compared to conventional error-free digital storage, our method reduces the memory footprint by up to one order of magnitude, without significantly compromising the stored model’s accuracy. -
Due to its high performance and decreasing cost per bit, flash storage is the main storage medium in datacenters for hot data. However, flash endurance is a perpetual problem, and due to technology trends, subsequent generations of flash devices exhibit progressively shorter lifetimes before they experience uncorrectable bit errors. In this paper, we propose addressing the flash lifetime problem by allowing devices to expose higher bit error rates. We present DIRECT, a set of techniques that harnesses distributed-level redundancy to enable the adoption of new generations of denser and less reliable flash storage technologies. DIRECT does so by using an end-to-end approach to increase the reliability of distributed storage systems. We implemented DIRECT on two real-world storage systems: ZippyDB, a distributed key-value store in production at Facebook and backed by RocksDB, and HDFS, a distributed file system. When tested on production traces at Facebook, DIRECT reduces application-visible error rates in ZippyDB by more than 100x and recovery time by more than 10,000x. DIRECT also allows HDFS to tolerate a 10,000--100,000x higher bit error rate without experiencing application-visible errors. By significantly increasing the availability and durability of distributed storage systems in the face of bit errors, DIRECT helps extend flash lifetimes.more » « less