Traditional SPM Research Articles

Scratchpad Memory Management Random Sampling Algorithm for Multi-core Processor

Traditional compiler-based SPM management often fails to accurately predict the memory access characteristics of system scheduling and task switching in a Multi-core Processor environment, thus affecting the effect of SPM management. The use of runtime dynamic detection can make up for this flaw and provide an accurate and efficient dynamic management method. This research focuses on the analysis of the similarities and differences between SPM management in Multi-core Processor environment and single-task environment, and builds a real-time operating system (RTOS) supporting multi-task scheduling according to experimental requirements, which is necessary for the random sampling of SPM allocation algorithm and improvements to meet the needs of adaptive SPM allocation for program runtime in a Multi-core Processor environment. The performance of the random sampling algorithm in Multi-core Processor environment is analyzed which proves the effectiveness of the allocation algorithm for Multi-core Processor environment.

Identity-mapping cascaded network for fMRI registration

Neuroscience researches based on functional magnetic resonance imaging (fMRI) rely on accurate inter-subject image registration of functional regions. The intersubject alignment of fMRI can improve the statistical power of group analyses. Recent studies have shown the deep learning-based registration methods can be used for registration. In our work, we proposed a 30-Identity-Mapping Cascaded network (30-IMCNet) for rs-fMRI registration. It is a cascaded network that can warp the moving image progressively and finally align to the fixed image. A Combination unit with an identity-mapping path is added to the inputs of each IMCNet to guide the network training. We implemented 30-IMCNet on an rs-fMRI dataset (1000 Functional Connectomes Project dataset) and a task-related fMRI dataset (Eyes Open Eyes Closed fMRI dataset). To evaluate our method, a group-level analysis was implemented in the testing dataset. For rs-fMRI, the criterions such as peak t-value of group-level t-maps, cluster-level evaluation, and intersubject functional network correlation were used to evaluate the quality of the registrations. For task-related fMRI, peak t-value in ALFF paired-t map and peak t-value in ReHo paired-t maps were used. Compared with traditional algorithm FSL, SPM, and deep learning algorithm Kim et al, Zhao et al our method has improvements of 48.90%, 30.73%, 36.38%, and 16.73% in the peak t value of t-maps. Our proposed method can achieve superior functional registration performance and thus gain a significant improvement in functional consistency.

A novel estimation method for SPM in China eastern coastal waters based on conventional hydrological profile measurements

Suspended particulate matter concentration (SPM) in coastal waters is of great importance for studying sediment resuspension and sediment transportation, especially for the profile distribution in bodies of water. The traditional SPM profile-obtaining method that uses a turbidity meter introduces large uncertainty for pigment particle-dominated waters. This research used a large amount of profile data on optical properties and hydrological measurements parameters (conductivity-temperature-depth (CTD), chlorophyll and turbidity), which were measured synchronously in the Bohai Sea and Yellow Sea; the data were used to analyze the relationships between the vertical distribution of the particulate backscattering ratio and the vertical distribution of pycnocline, chlorophyll and turbidity and to distinguish pigment particles and sediment particles in the vertical distribution. After considering the particle types, we also developed a novel method that exclusively depended on conventional hydrological measurements. The results show that the new method is simplified and effective and could significantly improve the accuracy of SPM estimations in coastal waters.

Efficiently Updating the Discovered Sequential Patterns for Sequence Modification

Mining sequential patterns (SPs) is a popular data mining task, which consists in finding interesting, unexpected, and useful patterns in sequence databases. It has several applications in many domains. However, most sequential pattern mining algorithms assume that databases are static, i.e. that they do not change over time. But in real-word applications, sequences are often modified. Thus, it is an important issue to design algorithms for updating SPs in a dynamic database environment. Although some algorithms have been proposed to maintain SPs in dynamic databases, these algorithms may have poor performance, especially when databases contain long sequences or a large number of sequences. This paper addresses this issue by proposing a novel dynamic mining approach named PreFUSP-TREE-MOD to address the problem of maintaining and updating discovered SPs when sequences in a database are modified. The proposed approach adopts the previously proposed pre-large concept using two support thresholds, to avoid scanning the database when possible, for updating the set of discovered patterns. Due to the pruning properties of the pre-large concept, the PreFUSP-TREE-MOD maintenance algorithm can effectively reduce the cost of database scans to maintain and update the built FUSP-tree for sequence modification. When the number of modified sequences is less than the safety bound of the pre-large concept, the proposed maintenance algorithm outperforms traditional SPM algorithms in batch mode, and the state-of-the-art maintenance algorithm in terms of execution time and number of tree nodes.

SPMCloud

The era of cloud computing on-a-chip is enabled by the aggressive move towards many-core platforms and the rapid adoption of Network-on-Chips. As a result, there is a need for large-scale distributed on-chip shared memories that are reliable, low power, and seamlessly manageable. In this work, we propose SPMCloud , a novel scratchpad-memory-based cloud-inspired volatile storage subsystem designed to meet the needs of future-generation many-core platforms. SPMCloud is composed of several concepts, including: (1) a highly scalable data-center-like memory subsystem that exploits two enterprise-network-inspired memory configurations, namely, embedded Network Attached Storage ( eNAS ) and embedded Storage Area Network ( eSAN ), and (2) on-demand allocation of reliable memory space through memory virtualization and the use of embedded RAIDs. Our experimental results on Mediabench/CHStone benchmarks show that the SPMCloud 's fully distributed reliable memory subsystems can achieve 48% energy savings and 70% latency reduction on average over state-of-the-art NoC memory reliability techniques. We then evaluate the scalability of the SPMCloud and compare it with traditional SPM allocation policies. The SPMCloud 's dynamic allocator outperforms the best competition by an average 60% ( eNAS ) and 46% ( eSAN ) when the platform runs at 250 MHz and by an average 80% ( eNAS ) and 40% when running at 1 GHz. Moreover, the SPMCloud achieves an average 83% energy savings across all configurations (number of cores) with respect to the best competitors when running at 250 MHz and 1 GHz. We then studied the SPM hit ratio across the various allocation policies discussed in this article and showed that on average the SPMCloud 's priority-driven dynamic allocation policy achieves 93.5% SPM hit ratio, 0.6% higher hit ratio than the closest allocation policy. We then showed that the eNAS and eSAN achieve an average of 67.9% and 29% reduction in execution time, respectively, over the best competitor. Similarly, the eNAS and eSAN achieve an average of 82.7% and 82.3% energy savings, respectively, over the best competitor. Furthermore, we evaluated the scalability of the SPMCloud and its performance/energy efficiency when providing support for some of the heavier E-RAID levels, and showed that the eNAS / eSAN configurations with SECDED achieve an average of 51.5% and 34.9% reduction in execution time, respectively, over the best competitor with SECDED. Similarly, the eNAS / eSAN configurations with E-RAID Level 1, + SECDED achieve an average of 82.3% and 75.6% energy savings, respectively, over the best competitor.

Novel Clean Concept of Advanced Patterning Film (Amorphous Carbon) for Beyond 2xnm Generation Self-Aligned Double-Patterning (SADP) Process

Advanced Patterning Film (APF, Amorphous Carbon) is newly developed hard mask material by APPLY MATERIALS, Inc. for fine pattern definition, especially used in ArF immersion process. However, amorphous carbon is one candidate of core materials of self align double pattering (SADP) process, usually suggested not to use wet clean process after patter definition due to moisture absorption of APF. We successfully demonstrate better amorphous carbon surface clean performance without any film damaged and line edge roughness (LER) improve 18.2% CD variation, 1.1nm in space even-odd bias beyond 28nm generation. APF of APPLY MATERIALS, Inc. is chemical vapor deposition (CVD) amorphous carbon (a-C) which precursors are normally acetylene (C2H2) and propane (C3H6). Traditional post clean SPM chemical consists of sulfuric acid (H2SO4) and hydro peroxide (H2O2). Hydro peroxide will oxidize amorphous carbon into CO or CO2and result in pattern damaged. We surveyed some post clean candidates in semiconductor fabrication common used, as table 1 shows. Only APM and DHF showed miner or no etching rate to amorphous carbon film. APM is first chosen chemical for amorphous carbon core post etching clean. In Figure 1-a, 3nm/side etching polymer is found on a-C sidewall, and Figure 1-b shows that dry etching polymer are totally removed after APM 10 minutes treatment. However, in SADP process, core material should be with higher removal rate than spacer material, which is usually selected by high temperature deposition film to achieve the high selectivity to core material in core removal process.As Figure 2 shows, amorphous carbon with C2H2precursor is porous structure. 10 minutes APM process will induce moisture absorption by porous amorphous carbon film and line twist in following high temperature spacer material deposition, 450C atomic layer deposition silicon nitride, shows as Figure 3-a. Figure 3-b shows worse even-odd spacer bias after SADP spacer defined. Shorter clean process time and high clean efficiency become the keys of a-C core post clean step. Two chemicals A and B, A is higher fluorine concentration contained and B is lower fluorine concentration contained, a-C core post clean efficiency were investigated and both process times are confined within 90 seconds, including rinse and drying steps. Figure 4-a., 4-b. and 4-c show chemical A has better polymer removal capability than chemical B. Line edge roughness (LER) is reduced from 3.03nm to 2.48nm, 18.2% improvement, shows as Figure 5. In Figure 6 good LER and even-odd space performance of SADP gate definition after adopting chemical A for a-C post etching clean. Long time clean process will result in water absorption of amorphous carbon film due to its porous structure, and will cause worse line edge roughness (LER) in the following high temperature spacer material deposition process. Shorten clean process time to avoid water absorption and improve clean efficiency are the major criteria to achieve successful amorphous carbon clean. Novel a-C clean method by raising F concentration to achieve higher clean efficiency and successfully improve LER 18.2% after core etching and post clean in positive tone SADP process beyond 2xnm generation.

Cleaning induced imprint template erosion

We studied the erosion and feature stability of fused silica patterns under different template cleaning conditions. The conventional sulfuric acid and hydrogen peroxide mixture (SPM) cleaning is compared with an advanced nonacid process. Spectroscopic ellipsometry optical critical dimension measurements were used to characterize the changes in pattern profile with good sensitivity. This study confirmed the erosion of the silica patterns in the traditional acid-based SPM cleaning mixture (H 2 SO 4 +H 2 O 2 ) at a rate of ∼0.1 nm per cleaning cycle. However, the advanced nonacid cleaning process only showed critical dimension shift of ∼0.01 nm per cleaning. Contamination removal and pattern integrity of sensitive 20-nm features under MegaSonic assisted cleaning was also demonstrated.

Covariance PET patterns in early Alzheimer's disease and subjects with cognitive impairment but no dementia: utility in group discrimination and correlations with functional performance

Although multivariate analytic techniques might identify diagnostic patterns that are not captured by univariate methods, they have rarely been used to study the neural correlates of Alzheimer's disease (AD) or cognitive impairment. Nonquantitative H 2 15O PET scans were acquired during rest in 17 probable AD subjects selected for mild severity [mean-modified Mini Mental Status Examination (mMMS) 46/57; SD 5.1], 16 control subjects (mMMS 54; SD 2.5) and 23 subjects with minimal to mild cognitive impairment but no dementia (mMMS 53; SD 2.8). Expert clinical reading had low success in discriminating AD and controls. There were no significant mean flow differences among groups in traditional univariate SPM Noxel-wise analyses or region of interest (ROI) analyses. A covariance pattern was identified whose mean expression was significantly higher in the AD as compared to controls ( P = 0.03; sensitivity 76–94%; specificity 63–81%). Sites of increased concomitant flow included insula, cuneus, pulvinar, lingual, fusiform, superior occipital and parahippocampal gyri, whereas decreased concomitant flow was found in cingulate, inferior parietal lobule, middle and inferior frontal, supramarginal and precentral gyri. The covariance analysis-derived pattern was then prospectively applied to the cognitively impaired subjects: as compared to subjects with Clinical Dementia Rating (CDR) = 0, subjects with CDR = 0.5 had significantly higher mean covariance pattern expression ( P = 0.009). Expression of this pattern correlated inversely with Selective Reminding Test total recall ( r = −0.401, P = 0.002), delayed recall ( r = −0.351, P = 0.008) and mMMS scores ( r = −0.401, P = 0.002) in all three groups combined. We conclude that patients with AD may differentially express resting cerebral blood flow covariance patterns even at very early disease stages. Significant alterations in expression of resting flow covariance patterns occur even for subjects with cognitive impairment. Expression of covariance patterns correlates with cognitive and functional performance measures, holding promise for meaningful associations with underlying biopathological processes.

STUDY OF TRACE ELEMENTS IN CELLS USING SPM, SR-XRM AND PIXE

Trace elements play important roles in cells. Nuclear techniques as traditional PIXE, SPM and SR-XRM provide solid tools for quantitative element analysis. The article presents element-distribution maps of endometrium, nerve cell and relative quantity tables. Advantages of PIXE, SPM and SR-XRM techniques, especially in application to cell biology, are discussed. PIXE has a large beam and is convenient in measuring a large quantity of samples. SPM gives element-distribution maps owing to its high resolution. SR-XRM tells quantity of elements by its good sensitivity and nondestructive irradiation. The combination of PIXE, SPM and SR-XRM demonstrates that Zn is a component of cell membrane and is proved to be a complementary way which will open vast vistas for cell analysis.