Exploiting Inter- and Intra-Memory Asymmetries for Data Mapping in Hybrid Tiered-Memories

Modern computing systems are embracing hybrid memory comprising of DRAM and non-volatile memory (NVM) to combine the best properties of both memory technologies, achieving low latency, high reliability, and high density. A prominent characteristic of DRAM-NVM hybrid memory is that it has NVM access latency much higher than DRAM access latency. We call this inter-memory asymmetry. We observe that parasitic components on a long bitline are a major source of high latency in both DRAM and NVM, and a significant factor contributing to high-voltage operations in NVM, which impact their reliability. We propose an architectural change, where each long bitline in DRAM and NVM is split into two segments by an isolation transistor. One segment can be accessed with lower latency and operating voltage than the other. By introducing tiers, we enable non-uniform accesses within each memory type (which we call intra-memory asymmetry), leading to performance and reliability trade-offs in DRAM-NVM hybrid memory. We extend existing NVM-DRAM OS in three ways. First, we exploit both inter- and intra-memory asymmetries to allocate and migrate memory pages between the tiers in DRAM and NVM. Second, we improve the OS's page allocation decisions by predicting the access intensity of a newly-referenced memory page in a program and placing it to a matching tier during its initial allocation. This minimizes page migrations during program execution, lowering the performance overhead. Third, we propose a solution to migrate pages between the tiers of the same memory without transferring data over the memory channel, minimizing channel occupancy and improving performance. Our overall approach, which we call MNEME, to enable and exploit asymmetries in DRAM-NVM hybrid tiered memory improves both performance and reliability for both single-core and multi-programmed workloads.Comment: 15 pages, 29 figures, accepted at ACM SIGPLAN International Symposium on Memory Managemen

A heterochromatic histone methyltransferase lowers nucleosome occupancy at euchromatic promoters

H3K9me3 (histone H3 modified with tri-methylation at lysine 9) is a hallmark of transcriptional silencing and heterochromatin. However, its global effects on the genome, including euchromatin, are less well understood. Here we develop Formaldehyde-Assisted Identification of Regulatory Elements (FAIRE) for C. elegans to examine the chromatin configuration of mutants that lack virtually all H3K9me3, while leaving H3K9me1 and H3K9me2 intact. We find that nucleosomes are mildly disrupted, and levels of H3K9me2 and H3K27me3 rise in mutant embryos. In addition to these expected changes, the most dramatic change occurs in euchromatin: many regions encompassing transcription start sites (TSSs) gain an average of two nucleosomes in mutants. The affected regions normally lack H3K9me3, revealing a locus non-autonomous role for H3K9me3. Affected TSSs are associated with genes that are active in epithelia and muscles, and implicated in development, locomotion, morphogenesis and transcription. Mutant embryos develop normally under ideal laboratory conditions but die when challenged, with defects in morphogenesis and development. Our findings reveal that H3K9me3 protects transcription start sites within euchromatin from nucleosome deposition. These results may be relevant to mammals, where diseases that disrupt the nuclear lamina and heterochromatin can alter epithelial and muscle gene expression

Improving Phase Change Memory Performance with Data Content Aware Access

A prominent characteristic of write operation in Phase-Change Memory (PCM) is that its latency and energy are sensitive to the data to be written as well as the content that is overwritten. We observe that overwriting unknown memory content can incur significantly higher latency and energy compared to overwriting known all-zeros or all-ones content. This is because all-zeros or all-ones content is overwritten by programming the PCM cells only in one direction, i.e., using either SET or RESET operations, not both. In this paper, we propose data content aware PCM writes (DATACON), a new mechanism that reduces the latency and energy of PCM writes by redirecting these requests to overwrite memory locations containing all-zeros or all-ones. DATACON operates in three steps. First, it estimates how much a PCM write access would benefit from overwriting known content (e.g., all-zeros, or all-ones) by comprehensively considering the number of set bits in the data to be written, and the energy-latency trade-offs for SET and RESET operations in PCM. Second, it translates the write address to a physical address within memory that contains the best type of content to overwrite, and records this translation in a table for future accesses. We exploit data access locality in workloads to minimize the address translation overhead. Third, it re-initializes unused memory locations with known all-zeros or all-ones content in a manner that does not interfere with regular read and write accesses. DATACON overwrites unknown content only when it is absolutely necessary to do so. We evaluate DATACON with workloads from state-of-the-art machine learning applications, SPEC CPU2017, and NAS Parallel Benchmarks. Results demonstrate that DATACON significantly improves system performance and memory system energy consumption compared to the best of performance-oriented state-of-the-art techniques.Comment: 18 pages, 21 figures, accepted at ACM SIGPLAN International Symposium on Memory Management (ISMM

Development of a thulium (Tm:YAP) laser system for brain tissue ablation

In this study, a thulium (Tm:YAP) laser system was developed for brain surgery applications. As the Tm:YAP laser is a continuous-wave laser delivered via silica fibers, it would have great potential for stereotaxic neurosurgery with highest local absorption in the IR region. The laser system developed in this study allowed the user to set the power level, exposure time, and modulation parameters (pulse width and on-off cycles). The Tm:YAP laser beam (200-600 mW, 69-208 W/cm 2) was delivered from a distance of 2 mm to cortical and subcortical regions of ex-vivo Wistar rat brain tissue samples via a 200-μm-core optical fiber. The system performance, dosimetry study, and ablation characteristics of the Tm:YAP laser were tested at different power levels by maximizing the therapeutic effects and minimizing unwanted thermal side-effects. The coagulation and ablation diameters were measured under microscope. The maximum ablation efficiency (100 × ablation diameter/coagulation diameter) was obtained when the Tm:YAP laser system was operated at 200 mW for 10 s. At this laser dose, the ablation efficiency was found to be 71.4% and 58.7% for cortical and subcortical regions, respectively. The fiber-coupled Tm:YAP laser system in hence proposed for the delivery of photothermal therapies in medical applications. © 2011 Springer-Verlag London Ltd

Accelerating read mapping with FastHASH

With the introduction of next-generation sequencing (NGS) technologies, we are facing an exponential increase in the amount of genomic sequence data. The success of all medical and genetic applications of next-generation sequencing critically depends on the existence of computational techniques that can process and analyze the enormous amount of sequence data quickly and accurately. Unfortunately, the current read mapping algorithms have difficulties in coping with the massive amounts of data generated by NGS. We propose a new algorithm, FastHASH, which drastically improves the performance of the seed-and-extend type hash table based read mapping algorithms, while maintaining the high sensitivity and comprehensiveness of such methods. FastHASH is a generic algorithm compatible with all seed-and-extend class read mapping algorithms. It introduces two main techniques, namely Adjacency Filtering, and Cheap K-mer Selection. We implemented FastHASH and merged it into the codebase of the popular read mapping program, mrFAST. Depending on the edit distance cutoffs, we observed up to 19-fold speedup while still maintaining 100% sensitivity and high comprehensiveness. © 2013 Xin et al

Mutation of Directed Graphs -- Corresponding Regular Expressions and Complexity of Their Generation

Directed graphs (DG), interpreted as state transition diagrams, are traditionally used to represent finite-state automata (FSA). In the context of formal languages, both FSA and regular expressions (RE) are equivalent in that they accept and generate, respectively, type-3 (regular) languages. Based on our previous work, this paper analyzes effects of graph manipulations on corresponding RE. In this present, starting stage we assume that the DG under consideration contains no cycles. Graph manipulation is performed by deleting or inserting of nodes or arcs. Combined and/or multiple application of these basic operators enable a great variety of transformations of DG (and corresponding RE) that can be seen as mutants of the original DG (and corresponding RE). DG are popular for modeling complex systems; however they easily become intractable if the system under consideration is complex and/or large. In such situations, we propose to switch to corresponding RE in order to benefit from their compact format for modeling and algebraic operations for analysis. The results of the study are of great potential interest to mutation testing

A Comparative Study between Two Regression Methods on LiDAR Data: A Case Study

Airborne LiDAR (Light Detection and Ranging) has become an excellent tool for accurately assessing vegetation characteristics in forest environments. Previous studies showed empirical relationships between LiDAR and field-measured biophysical variables. Multiple linear regression (MLR) with stepwise feature selection is the most common method for building estimation models. Although this technique has provided very interesting results, many other data mining techniques may be applied. The overall goal of this study is to compare different methodologies for assessing biomass fractions at stand level using airborne Li- DAR data in forest settings. In order to choose the best methodology, a comparison between two different feature selection techniques (stepwise selection vs. genetic-based selection) is presented. In addition, classical MLR is also compared with regression trees (M5P). The results when each methodology is applied to estimate stand biomass fractions from an area of northern Spain show that genetically-selected M5P obtains the best results

Aging-Aware Request Scheduling for Non-Volatile Main Memory

Modern computing systems are embracing non-volatile memory (NVM) to implement high-capacity and low-cost main memory. Elevated operating voltages of NVM accelerate the aging of CMOS transistors in the peripheral circuitry of each memory bank. Aggressive device scaling increases power density and temperature, which further accelerates aging, challenging the reliable operation of NVM-based main memory. We propose HEBE, an architectural technique to mitigate the circuit aging-related problems of NVM-based main memory. HEBE is built on three contributions. First, we propose a new analytical model that can dynamically track the aging in the peripheral circuitry of each memory bank based on the bank's utilization. Second, we develop an intelligent memory request scheduler that exploits this aging model at run time to de-stress the peripheral circuitry of a memory bank only when its aging exceeds a critical threshold. Third, we introduce an isolation transistor to decouple parts of a peripheral circuit operating at different voltages, allowing the decoupled logic blocks to undergo long-latency de-stress operations independently and off the critical path of memory read and write accesses, improving performance. We evaluate HEBE with workloads from the SPEC CPU2017 Benchmark suite. Our results show that HEBE significantly improves both performance and lifetime of NVM-based main memory.Comment: To appear in ASP-DAC 202