Interlaced Magnetic Recording Research Articles

Optimizing Secure Deletion in Interlaced Magnetic Recording With Move-on-Cover Approach

Optimizing Secure Deletion in Interlaced Magnetic Recording With Move-on-Cover Approach

FSIMR: File-system-aware Data Management for Interlaced Magnetic Recording

Interlaced Magnetic Recording (IMR) is an emerging recording technology for hard-disk drives (HDDs) that provides larger storage capacity at a lower cost. By partially overlapping (interlacing) each bottom track with two adjacent top tracks, IMR-based HDDs successfully increase the data density while incurring some hardware write constraints. To update each bottom track, the data on two adjacent top tracks must be read and rewritten to avoid losing their valid data, resulting in additional overhead for performing read-modify-write (RMW) operations. Therefore, researchers have proposed various data management schemes to mitigate such overhead in recent years, aiming at improving the write performance. However, these designs have not taken into account the data characteristics of the file system, which is a crucial layer of operating systems for storing/retrieving data into/from HDDs. Consequently, the write performance improvement is limited due to the unawareness of spatial locality and hotness of data. This paper proposes a file-system-aware data management scheme called FSIMR to improve system write performance. Noticing that data of the same directory may have higher spatial locality and are mostly updated at the same time, FSIMR logically partitions the IMR-based HDD into fixed-sized zones; data belonging to the same directory will be arranged to one zone to reduce the time of seeking to-be-updated data (seek time). Furthermore, cold data within a zone are arranged to bottom tracks and updated in an out-of-place manner to eliminate RMW operations. Our experimental results show that the proposed FSIMR could reduce the seek time by up to 14% without introducing additional RMW operations, compared to existing designs.

Balloon: An Elastic Data Management Strategy for Interlaced Magnetic Recording

Recently, the emerging technology known as Interlaced Magnetic Recording (IMR) has been receiving widespread attention from both industry and academia. IMR-based disks incorporate interlaced track layouts and energy-assisted techniques to dramatically increase areal densities. The interlaced track layout means that in-place updates to the bottom track require rewriting the adjacent top track to ensure data consistency. However, at high disk utilization, frequent track rewrites degrade disk performance. To address this problem, we propose a solution called Balloon to reduce the frequency of track rewrites. First, an adaptive write interference data placement policy is introduced, which judiciously places data on tracks with low rewrite probability to avoid unnecessary rewrites. Next, an on-demand data shuffling mechanism is designed to reduce user-requests write latency by implicitly migrating data and promptly swapping tracks with high update block coverage to the top track. Finally, a write-interference-free persistent buffer design is proposed. This design dynamically adjusts buffer admission constraints and selectively evicts data blocks to improve the cooperation between data placement and data shuffling. Evaluation results show that Balloon significantly improves the write performance of IMR-based disks at medium and high utilization compared with state-of-the-art studies.

Leveraging Journaling File System for Prompt Secure Deletion on Interlaced Recording Drives

With the growing awareness of secure computation, more and more users want to make their digital footprints securely deleted and irrecoverable after updating or removing files on storage devices. To achieve the effect of secure deletion, overwritten-based secure deletion techniques have been proposed to overwrite invalidated storage space with scrambled data content. Nevertheless, overwritten-based secure deletion requires explicit write requests for rewriting invalidated storage space with random data, thus incurring additional internal write traffic on storage devices. Recently, this inefficient aspect of secure deletion is exacerbated by the emergence of high-density interlaced magnetic recording (IMR) technology. IMR technology enhances the storage density of hard disk drives by interlacing narrower top tracks on wider bottom tracks. Owing to the interlaced track layout, securely erasing invalidated data on bottom tracks interferes with adjacent top tracks and track rewrites are required to preserve valid data on top tracks; thus, overwritten-based secure deletion on IMR drives significantly enlarges the internal write traffic and impairs the secure deletion efficiency. In this paper, instead of directly alleviating the constraint induced by the interlaced track layout, we propose leveraging the interlaced track layout of IMR drives in combination with the journaling data stream of journaling file systems to enable prompt secure data deletion while minimizing the write traffic of secure deletion operations. Experimental results suggest that the performance improvement achieve by the proposed prompt secure deletion (P-SD) strategy is 51.84% on average, when compared with the previous TrackLace approach on IMR drives.

Improved Recording Performance With Writer Design and Joint Learning-Based Neural Network for Heat-Assisted Interlaced Magnetic Recording

Heat-assisted interlaced magnetic recording (HIMR) further increases the areal density with the interlaced track layout architecture compared to conventional heat-assisted magnetic recording. However, besides the 2-D inter-symbol interference (ISI) and thermal jitters, the transition curvatures due to the circular thermal profile cause severe erasures after write and obvious nonlinear distortions of readback signals. This deteriorates the recording performance severely. Especially the degrees of transition curvatures for the low temperature written track (LT) and high temperature written track (HT) are distinct, which makes the correction of transition curvature with only the writer design impossible. Correspondingly, a comprehensive method consisting of writer design and multitrack detection algorithm with joint learning-based neural network (JLNN) is proposed to mitigate the effects of transition curvature and 2-D ISI for both LT and HT of HIMR. First, a designed writer with splitting main poles produces the spatially nonuniform write field along the crosstrack direction to correct the transition curvature of LT. Then the multitrack detection with JLNN and improved Bahl–Cocke–Jelinek–Raviv (BCJR) detector (JLNN-IB) algorithm is studied to further mitigate the effects of residual transition curvatures, thermal jitters, and 2-D ISI for both HT and LT. Specifically, the readback signals of read head array and decoded log-likelihood ratio (LLR) outputted by the low-density parity check (LDPC) decoder are fed into JLNN to obtain the equalized signal and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$a$ </tex-math></inline-formula> <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">priori</i> probability (AP) of three tracks. Then the equalized signal as well as AP of current track and corresponding soft bit estimations of adjacent tracks are embedded into the branch metrics of improved BCJR detector for data detection, and the LDPC decoder is cascaded for the error correction. The simulation indicates that at the recording density of 2.11 Tb/in <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , the proposed comprehensive writer design and JLNN-IB algorithm provide 9.2 and 9.7 dB signal to noise ratio (SNR) gains compared to the conventional 2-D neural network equalizer and 2-D linear equalizer under the uniform write field and circular thermal profile, respectively.

Detection Scheme With Joint Intertrack Interference and Media Noise Mitigations for Heat Assisted Interlaced Magnetic Recording

Heat assisted interlaced magnetic recording (HIMR) is a promising candidate for the next-generation of magnetic recording technology to further increase the area density beyond 1Tb/in <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . Specifically, the high temperature and low temperature tracks are written in an interlaced order to improve the recording performance. However, the inter-track interference (ITI), inter-symbol interference (ISI) and thermal jitters brought by the increased recording density and Curie temperature variations are severe in HIMR, which degrade the bit error rate (BER) performance obviously. In this study, we propose a multitrack detection scheme with joint intertrack interference and media noise mitigations. Here a multi-task neural network (MTNN) is designed to simultaneously predict ITI pattern and residual media noise, then the 2D variable equalizers corresponding to different ITI patterns are implemented and predicted residual media noises are embedded into the branch metrics of modified Bahl-Cocke-Jelinek-Raviv (BCJR) detector to mitigate ITI and whiten media noise. The simulation demonstrates that the proposed MTNN with variable equalizer and modified BCJR detector (MTNN+VE+MB) algorithm mitigates the ITI and media noise effectively. At the channel bit density of 3.10 Tb/in <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , it provides 2.6 dB signal-to-noise ratio (SNR) gain compared to that of conventional 2D fixed equalizer with pattern dependent noise prediction detector (FE+PDNP) for the low temperature (LT) tracks with 4% Curie temperature variance.

TrackLace: Data Management for Interlaced Magnetic Recording

Interlaced Magnetic Recording (IMR) is a promising technology which achieves higher data density and lower write amplification (WA) than Shingled Magnetic Recording (SMR). In IMR, top tracks and bottom tracks are interlaced so each bottom track is partially overlapped with two adjacent top tracks. Top tracks can be updated without any WA, but bottom track updates require reading and rewriting of affected valid data on the two neighboring top tracks. There are few published studies discussing WA in IMR drives. We propose TrackLace to reduce WA for IMR. TrackLace consists of three techniques: Z-Alloc allocates user data to the tracks in alternating directions and spreads unallocated tracks among allocated tracks; Top-Buffer opportunistically utilizes unallocated top tracks to buffer bottom track updates; and Block-Swap progressively swaps bottom track hot data with top track cold data during high space utilization. To further optimize TrackLace performance, we propose a virtual frame design that can keep the relocated block (due to Top-Buffer or Block-Swap) close to its original location and an adaptive buffering mechanism that can avoid unnecessary redirections depending on the write locality. Evaluations show that TrackLace can reduce WA by 45 percent and lower average latency by 31percent compared with baseline schemes.

MAGIC: Making IMR-Based HDD Perform Like CMR-Based HDD

The past decades have witnessed the tremendous success of Conventional Magnetic Recording (CMR)-based Hard Disk Drives (HDDs) in data storage. To eliminate the bottleneck of CMR-based HDDs in providing higher areal density, an emerging Interlaced Magnetic Recording (IMR) is capable of achieving higher areal density with limited changes to disk makeup. Nevertheless, existing approaches for IMR-based HDDs may suffer serious read and write performance degradation as compared with CMR-based HDDs. Thus, this article presents a device-level solution, namely <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MAGIC</i> translation layer, which aims at <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><u>MA</u></b> kin <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><u>G</u></b> <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><u>I</u></b> MR-based HDDs perform like <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><u>C</u></b> MR-based HDDs in terms of comparable access performance. Specifically, not merely trying to improve the performance of raw IMR-based HDDs, this work, for the first time, moves one step forward to minimize the performance gap between IMR and CMR-based HDDs. Technically, by 1) fully utilizing two special CMR-like potentials of IMR and 2) gracefully trading the sequential access performance as space usage increases, MAGIC minimizes track rewriting overheads to achieve CMR-like performance. Our results reveal that MAGIC not only improves the write performance compared with existing designs, but also has potential to approach read and write performance of CMR-based HDD.

Multitrack Detection With a Two-Dimensional Soft-Transition Assisted Multitask Neural Network for Heat-Assisted Interlaced Magnetic Recording

Heat-assisted interlaced magnetic recording (HIMR) further increases recording density compared to heat-assisted magnetic recording due to the interlaced track layout. However, the smaller circular thermal profile of the top low-temperature-written tracks results in severe transition curvatures, which causes nonlinear distortions of the readback signal and degrades the bit error rate (BER) performance. Moreover, the increased recording density causes severe two-dimensional (2-D) intersymbol interference (ISI) along both down track and cross track directions. To mitigate the effect of nonlinear distortion and 2-D ISI in an HIMR system, we model a 2-D soft-transition, information-assisted, multitask neural network and modified Bahl–Cocke–Jelinek–Raviv (BCJR) detector (2DST-MTNN-MB) algorithm to detect three tracks simultaneously. The readback signal and 2-D soft-transition information are fed into the multitask neural network to obtain equalized signals and soft bit estimates of three tracks simultaneously. Then, the signal of the current track and soft estimates of the side tracks are embedded into the branch metrics of the modified BCJR detector for data detection, and the low-density parity check decoder is cascaded for error correction. The simulation results show that the 2DST-MTNN-MB algorithm provides 5.0 dB signal-to-noise ratio gains with reduced computation complexity compared with a single-track, single-task neural network and one-dimensional BCJR detector algorithm for the low-temperature-written track at channel bit density of 3.51 Tb/in <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , thereby narrowing the gap of BER performance between high- and low-temperature-written tracks.

Joint Multi-Level Readback for Array-Reader-Based Interlaced Magnetic Recording

In this study, a novel joint multi-track multi-level (MTML) read channel signal processing scheme is proposed to enhance the data transfer rate in an array-reader-based interlaced magnetic recording (ARIMR). Wide individual readers capture mixtures of multiple track contributions and proposed MTML read channel effectively disaggregates individual track data for joint track data retrieval in a single revolution. Numerical evaluations with the micro-pixelated magnetic channel model shows improvements of the cross-track profile of bit error rate with the proposed MTML-ARIMR approach for a dual-reader and triple-track readback configuration.

Multitrack Detection With 2-D Iterative Soft Estimate Aided Neural Network Equalizer for Heat-Assisted Interlaced Magnetic Recording

Heat-assisted interlaced magnetic recording (HIMR) with interlaced track layout architecture enables the further increased areal density compared to the conventional heat-assisted magnetic recording. However, the severe transition curvatures of low temperature written tracks cause noticeable nonlinear distortions of readback signal, and the 2-D intersymbol interference (ISI), media noise, and thermal jitter also bring the challenges for data recovery. Correspondingly, a multitrack detection scheme with 2-D iterative soft estimate aided neural network equalizer (2D-ISA NNE) is proposed for the HIMR system, which iteratively feeds back the soft estimate of reliable sidetracks’ information (e.g., high temperature written tracks) during the neural network equalization (NNE) of middle track (e.g., low temperature written track). Here, the Bahl–Cocke–Jelinek–Raviv (BCJR) detector and low-density parity-check (LDPC) decoder are utilized for the following data detection and error corrections. Then, the similar ISA NNE is implemented to recover the sidetracks’ data. It is found that the proposed 2D-ISA NNE algorithm mitigates the 2-D ISI and nonlinear distortion more effectively compared to the conventional 2-D linear equalizer (LE) and neural network equalizer (NNE). For HIMR at the channel bit density of 3.51 Tb/in2 and overlapping ratio of 0.46, the proposed 2D-ISA NNE algorithm significantly decreases the bit error rate gap between the low temperature and high temperature written tracks. For the low temperature written track, it provides 3.1 and 4 dB signal-to-noise ratio (SNR) gains compared to the conventional 2-D NNE and 2-D LE, respectively.

Single-reader dual-track readback scheme for synchronized interlaced magnetic recording

In this study, multi-level joint-track readback scheme is proposed for interlaced magnetic recording (IMR) with write synchronization. IMR typically provides an areal density capability (ADC) gain by pre-fixing the recording orders as interlaced and customizing the write configurations for neighboring tracks, such that narrow and wide tracks are interlaced. On the other hand, due to the unbalanced track widths in IMR, readback waveforms by a single wide reader covering two adjacent tracks can be decomposed into four distinguishable levels, when tracks are recorded in a synchronous manner. By taking advantage of the four level (4L) detecting capability, the single reader based dual-track readback (SR-DTR) IMR has a potential to provide a doubled data rate (2X) retrieval. For the feasibility test of the SR-DTR IMR, numerical simulations are conducted for bit-error rate (BER) evaluations by the micro-pixelated magnetic recording channel model. Partial response equalizer and Viterbi detector are modified for 4L readback waveforms, and are investigated with cross-track read offsets under various track and linear densities. BER bathtub investigation results show the feasibility of 2X retrievals by the SR-DTR IMR approach.

Perpendicular Interlaced Magnetic Recording

Perpendicular magnetic recording is the current generation hard disk drive technology, which enables the continued and significant growth of large storage systems in data centers. There are currently two common architectures for the layout of tracks in perpendicular hard disk drives: conventional magnetic recording (CMR) and shingled magnetic recording (SMR). In CMR, any track can be written at any time and neighboring tracks do not intentionally overlap. In SMR, the tracks are written sequentially in bands with the tracks intentionally overlapped like shingles on a roof. In this article, interlaced magnetic recording (IMR) architecture is applied with a perpendicular magnetic recording system. With Perpendicular Interlaced Magentic Recording (PIMR), we observed 2%–3% increase in areal density for single writer PIMR and 7%–20% increase in areal density for two writer PIMR over CMR whereas with SMR, we observed 19% increase in areal density over CMR.

Skew-Aware Joint Multi-Track Equalization for Array Reader-Based Interlaced Magnetic Recording

Interlaced magnetic recording (IMR) enhanced with an array reader, named array reader-based IMR (ARIMR), has been introduced recently showing a tangible areal density capability gain over the conventional recording system. Joint read equalization is one of the key enablers to improve the bit-error-rate performance of the readback signals, which even shows potential for on-line processing of joint multi-track retrievals. However, the performance gain of ARIMR may not be guaranteed for the entire disk due to wide variations of the cross-track separation (CTS) between read sensors by the skew of the array and recording tracks. In order to mitigate the undesired skew effect in ARIMR, a novel joint multi-track equalization scheme is proposed in this paper with customized allocation of the array reader depending on the skew as well as the joint track center. Furthermore, individual readers in the array are not necessarily identical and their performance difference should be accounted for together with CTS for reader allocations. Therefore, the effective joint center of the target tracks is estimated in the proposed study to allocate the array reader for jointly accessing multiple tracks in ARIMR, even with undesired track mis-registration offsets. For performance evaluation, the proposed joint equalization with effective cross-track center allocation scheme is investigated by numerical ARIMR channel simulations with the micro-pixelated magnetic channel model. In the evaluation, varying CTS conditions are simulated to account for the skew impacts on ARIMR reading dual tracks and the corresponding effective cross-track center for placing the reader. Overall, off-track capability widths common for the two neighboring tracks can be evaluated for a broad range of array readers, which shows the feasibility of joint reading of dual tracks by ARIMR.

Joint Equalization of Asynchronous Reads in Array-Reader-Based Interlaced Magnetic Recording

This paper proposes a joint read equalization scheme for interlaced magnetic recording (IMR) employing an array of readers, where multi-reader captured waveforms from asynchronously recorded tracks are jointly processed for single or multiple track data retrievals. In the array-reader-based IMR (ARIMR), the inter-track interference (ITI) collected from one reader is not necessarily synchronized to the other readers, especially in the case of a large cross-track separation (CTS) between the readers due to the linear density differentiation between the neighboring tracks. For the efficient mitigation of such asynchronous ITIs, an effective resampling-based joint equalization scheme is proposed in this paper, where multiple readbacks are digitally synchronized for designated target tracks, and joint processing of them suppresses the ITI in the equalized output. Furthermore, the proposed effective synchronization can be applied for joint multi-track retrievals when the CTS of the array reader is closed to the track pitch. For performance evaluations of the proposed joint read equalization scheme, numerical ARIMR channel simulations by the micro-pixelated magnetic channel model are conducted, and a bit error rate performance is evaluated under various configurations. In addition, waveforms captured from a dual-reader hard disk drive are evaluated with the proposed joint read equalization schemes for practical performance measurements of ARIMR. In both evaluations, unfavorable CTS conditions are investigated to account for the dominant skew effect in ARIMR, where the proposed joint equalization scheme enhances the off-track capability performance, especially with the customized configurations of interlaced recording. In overall, ARIMR with joint read equalization shows the potential of an areal density capability gain and a doubling of the data transfer rate over the conventional perpendicular magnetic recording and legacy IMR.

Areal Density Comparison Between Conventional, Shingled, and Interlaced Heat-Assisted Magnetic Recording With Multiple Sensor Magnetic Recording

Heat-assisted magnetic recording (HAMR) is the next-generation hard disk drive technology which enables continued and significant areal density growth. There are currently three write architectures for the layout of tracks in hard disk drives: conventional magnetic recording (CMR), shingled magnetic recording (SMR), and interlaced magnetic recording (IMR). The read-back architecture multiple-sensor magnetic recording (MSMR) can be combined with the three different write architectures to increase the areal density by using two or more readers to read-back the same track. In this paper, we compare the areal density capability of HAMR CMR, HAMR SMR, and HAMR IMR combined with read-back with one reader, MSMR with two readers, and MSMR with three readers.

Generalized Interlaced Magnetic Recording With Flexible Inter-Track Interference Cancellation

In this paper, interlaced magnetic recording (IMR) is generalized with a flexible inter-track interference cancellation (F-ITIC) scheme to enhance the overall areal density capability (ADC) by balancing and mitigating the mutual ITI between neighboring tracks. The IMR showed ADC gain by interlaced recording of aggressive bit density (BD) top and relaxed BD bottom tracks, where asynchronous ITI mitigation was applied to the bottom ones. On the other hand, IMR configuration can be generalized by the selective write width control, such that narrower relaxed BD top tracks are recorded over wider aggressive BD bottom tracks. In this generalized IMR (G-IMR), balanced ITI between interlaced tracks can provide ADC gain over legacy IMR (L-IMR) and customized F-ITIC for both tracks can further increase the gain. Note that the ITI processing scheme for G-IMR should be flexible in order to manage the ITI signals from high BD affecting low BD tracks, or vice versa. To evaluate the performance of G-IMR with the F-ITIC, numerical evaluations are conducted with the micro-pixelated magnetic channel model. The results show that G-IMR provides a favorable tradeoff between both tracks’ BDs and track density associated mutual ITIs, which offers a tangible ADC gain with the ITI cancellation over the L-IMR.

Adaptive Asynchronous Inter-Track Interference Cancellation for Interlaced Magnetic Recording with Random Frequency Offsets

In this paper, an adaptive inter-track interference (ITI) mitigating scheme is proposed for interlaced magnetic recording (IMR) with random frequency offsets. Recently, proposed IMR has a potential areal density capability gain over conventional perpendicular magnetic recording, as it involves writing tracks with differentiated linear densities in an interlaced manner, while suppressing the ITI efficiently during the reading operation via asynchronous ITI cancellation (A-ITIC). The A-ITIC estimates and subtracts the ITI contributions from its side tracks in the effectively synchronized domain via interpolation-filter-based relative timing adjustments. However, when the tracks are recorded with non-negligible random frequency offsets, the ITI response is averaged out, providing a weak estimate, and the A-ITIC-based bit error rate performance gain disappears. In order to compensate for these dynamic timing misalignments, an adaptive ITI mitigation scheme is proposed called an adaptive A-ITIC, where the ITI response is continuously updated via effective timing adjustments along the sector. Numerical evaluations using a micro-pixel-based magnetic channel model show that the legacy A-ITIC performs poorly for IMR with non-negligible random frequency offsets, whereas the proposed adaptive scheme compensates for most of the performance degradation by effectively tracing the relative timing shifts via adaptation measures.

Heat-Assisted Interlaced Magnetic Recording

Heat-assisted magnetic recording (HAMR) is the next generation hard disk drive technology that enables continued and significant areal density growth. There are currently two common architectures for the layout of tracks in hard disk drives: conventional magnetic recording (CMR) and shingled magnetic recording (SMR). In CMR, any track can be written at any time and neighboring tracks do not intentionally overlap. In SMR, the tracks are written sequentially in bands with the tracks intentionally overlapping like shingles on a roof. In this paper, we introduce a novel track layout, interlaced magnetic recording (IMR), and apply it to a HAMR recording system. With heat-assisted IMR, we observed a 31% increase in areal density over HAMR CMR whereas in a HAMR SMR architecture, we observed a 27% increase in areal density over HAMR CMR.

Architecture for Hard Disk Drives

Magnetic data storage has made rapid progress in terms of areal density over the past few decades. Current products have areal density levels that exceed 1012 bits per square inch, about 1000 times greater than areal densities of the mid-1990s. Five component technologies have become hard-disk-drive industry standards over the past two decades: read heads based on giant magnetoresistance or tunneling magnetoresistance, perpendicular write heads, perpendicular recording media, heaters, and contact detection sensors. At the recording system level, shingled magnetic recording has been implemented by all disk-drive companies, but it has not become a new standard due to the additional penalty in access time (or latency). Here, interlaced magnetic recording and blocked magnetic recording are introduced and compared with conventional and shingled magnetic recording.