GPU Based Acceleration Techniques: Algorithms, Implementations, and Applications

Shared memory many-core processors such as GPUs have been extensively used in accelerating computation-intensive algorithms and applications. When porting existing algorithms from sequential or other parallel architecture models to shared memory many-core architectures, non-trivial modifications are often needed to match the execution patterns of the target algorithms with the characteristics of many-core architectures. This dissertation presents a collection of methods and techniques for accelerating various important applications on GPU, including radiation dose calcula- tion, ray tracing based graphics rendering, and nearest neighbor search. Specifically, we study the performance issues of ray traversal in spatially decomposed scenes, and propose a new data structure, called Shell, to completely eliminate the expensive hierarchical search operations. We also develop an efficient GPU implementation of the Three Dimensional Digital Differential Analyzer (3D-DDA) algorithm, which avoids the overhead of execution divergence by replacing the nested conditional instruction- s with a set of simple operations. Those two methods are used to accelerate the Collapsed Cone Convolution Superposition (CCCS) algorithm, which is the clinical choice for dose calculation in radiation treatment planning systems. Furthermore, we present a locality enhancing method for Monte Carlo based ray tracing (MCBRT) algorithm on CPU-GPU heterogeneous systems, which improves the spatial and temporal data locality by organizing random rays into coherent groups. Finally, we propose a series of techniques to accelerate nearest neighbor search algorithm on GPU, including a GPU-cache efficient data structure (k-pack tree), a coherent parallel search algorithm, and a cost model based performance optimization method. For each of the target applications, our proposed approaches provide non-trivial performance speedup over the state-of-the-art work, e.g., 6–8X in Monte Carlo dose calculation, and 3.5–5.5X in graphics ray tracing. Our techniques can be implemented in various parallel programming models, such as CUDA and OpenCL, and applicable on many modern GPU architectures, including NVIDIA Kepler/Maxwell, AMD GCN, and Intel Xeon Phi

Nanoscale Probing of Electrical Memory Effects in van der Waals Layered PdSe₂

Tunable electronic materials that can be switched between different impedance states are fundamental to the hardware elements for neuromorphic computing architectures. This “brain-like” computing paradigm uses highly paralleled and colocated data processing, leading to greatly improved energy efficiency and performance compared to traditional architectures in which data have to be frequently transferred between processor and memory. In this work, we use scanning microwave impedance microscopy for nanoscale electrical and electronic characterization of two-dimensional layered semiconductor PdSe2 to probe neuromorphic properties. The local resolution of tens of nanometers reveals significant differences in electronic behavior between and within PdSe2 nanosheets (NSs). In particular, we detected both n-type and p-type behaviors, although previous reports only point to ambipolar n-type dominating characteristics. Nanoscale capacitance–voltage curves and subsequent calculation of characteristic maps revealed a hysteretic behavior originating from the creation and erasure of Se vacancies as well as the switching of defect charge states. In addition, stacks consisting of two NSs show enhanced resistive and capacitive switching, which is attributed to trapped charge carriers at the interfaces between the stacked NSs. Stacking n- and p-type NSs results in a combined behavior that allows one to tune electrical characteristics. As local inhomogeneities of electrical and electronic behavior can have a significant impact on the overall device performance, the demonstrated nanoscale characterization and analysis will be applicable to a wide range of semiconducting materials

Spatial Localization of Excitons and Charge Carriers in Hybrid Perovskite Thin Films

The fundamental photophysics underlying the remarkably high-power conversion efficiency of organic–inorganic hybrid perovskite-based solar cells has been increasingly studied using complementary spectroscopic techniques. However, the spatially heterogeneous polycrystalline morphology of the photoactive layers owing to the presence of distinct crystalline grains has been generally neglected in optical measurements; therefore, the reported results are typically averaged over hundreds or even thousands of such grains. Here we apply femtosecond transient absorption microscopy to spatially and temporally probe ultrafast electronic excited-state dynamics in pristine methylammonium lead tri-iodide (CH₃NH₃PbI₃) thin films and composite structures. We found that the electronic excited-state relaxation kinetics are extremely sensitive to the sample location probed, which was manifested by position-dependent decay time scales and transient signals. Analysis of transient absorption kinetics acquired at distinct spatial positions enabled us to identify contributions of excitons and free charge carriers

Synthesis of Few-Layer GaSe Nanosheets for High Performance Photodetectors

Two-dimensional (2D) semiconductor nanomaterials hold great promises for future electronics and optics. In this paper, a 2D nanosheets of ultrathin GaSe has been prepared by using mechanical cleavage and solvent exfoliation method. Single- and few-layer GaSe nanosheets are exfoliated on an SiO₂/Si substrate and characterized by atomic force microscopy and Raman spectroscopy. Ultrathin GaSe-based photodetector shows a fast response of 0.02 s, high responsivity of 2.8 AW^–1 and high external quantum efficiency of 1367% at 254 nm, indicating that the two-dimensional nanostructure of GaSe is a new promising material for high performance photodetectors

Additional file 1 of Tumor antigens and immune subtypes of glioblastoma: the fundamentals of mRNA vaccine and individualized immunotherapy development

Additional file 1: Figure S1. Identification of tumor antigens associated with GBM prognosis. Kaplan-Meier curves comparing RFS for groups with different expression of ADAMTSL4 (a), COL6A1 (b), CTSL (c), CYTH4 (d), EGFLAM (e), LILRB2 (f), MPZL2 (g), SAA2 (h), and LSP1 (i) in GBM. Red lines represented high gene expression, blue represented low gene expression. Figure S2. Identification of tumor antigens associated with infiltration of antigen-presenting cells in TCGA cohort. The correlation between the expression levels of ADAMTSL4 (a), COL6A1 (b), CTSL (c), CYTH4 (d), EGFLAM (e), LILRB2 (f), MPZL2 (g), SAA2 (h), and LSP1 (i) and infiltration levels of dendritic cells and macrophages in GBM. Figure S3. A two gene signature based on LSP1 and ADAMTSL4, risk score = LSP1*0.33421+ ADAMTSL4*0.12244. a Risk distribution, survival status and LSP1 and ADAMTSL4 expression in GBM patients. b Kaplan-Meier curve comparing OS of different risk in GBM patients. c ROC curve showing good predictive performance. Figure S4. Correlation between immune subtypes and prognosis of GBM. a Kaplan-Meier curve comparing OS of different immune subtypes in the TCGA cohort. b Kaplan-Meier curve comparing OS of different immune subtypes in the REMBRANDT cohort. Figure S5. Association of immune subtypes with TMB and mutation in GBM. TMB (a) and mutation number (b) of different immune subtypes in GBM. c The top 10 frequently mutated genes in GBM immune subtypes. Figure S6. Correlation between principal component 1/2 and 21 immune-related molecular signatures. Figure S7. Identification of functional immune genes modules in GBM. Cumulative distribution function curve (a), delta area curve (b), and consensus heatmap (c) of immune-related gene expression profile in the TCGA cohort. Figure S8. Relationship between GMs and prognosis of GBM patients in the TCGA cohort. Kaplan-Meier curves showing OS analysis of GM1 (a), GM3 (b), GM4 (c), GM5 (d), GM6 (e) and GM7 (f) in the TCGA cohort. Red lines represented high GM scores, blue represented low GM scores. Figure S9. Kaplan-Meier curve showing OS analysis of GM2 in the REMBRANDT cohort. Figure S10. Protein-protein interaction network for GM1 genes. Figure S11. Protein-protein interaction network for GM2 genes. Figure S12. Immune hub genes in GBM. a 51 hub genes in GM1. b The top 10 hub genes in GM2. Figure S13. KEGG pathway analysis of DEGs between responders and non-responders. a KEGG pathway analysis of DEGs in pre-anti-PD-1 treatment samples. b KEGG pathway analysis of DEGs in post-anti-PD-1 treatment samples. Figure S14. Seven candidate antigens detected in the TCGA cohort in relation to T cell receptors Shannon, richness and evenness. Figure S15. Association of immune subtypes with TMB and mutation in IDH-wildtype GBM. TMB (a) and mutation number (b) of different immune subtypes in IDH-wildtype GBM. Figure S16. Association between immune subtypes and immunomodulators in IDH-wildtype GBM. a Differences in expression levels of ICP-related genes among immune subtypes in IDH-wildtype GBM. b Differences in expression levels of ICD-related genes among immune subtypes in IDH-wildtype GBM. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Figure S17. Cellular and molecular characteristic of immune subtypes in IDH-wildtype GBM. a Heatmap of 28 previously reported immune cell signatures scores among immune subtypes in IDH-wildtype GBM. b Differences of 28 immune cell signatures scores among immune subtypes in IDH-wildtype GBM. c The distribution of IDH-wildtype GBM four immune subtypes in the pan-cancer immune subtypes. d 21 immune-related molecular signatures with significant differences among IDH-wildtype GBM immune subtypes. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Figure S18. The immune landscape of IDH-wildtype GBM. a The immune landscape of IDH-wildtype GBM. Each dot represents a patient, and different colors represent different immune subtypes. The horizontal axis represents the principal component 1, and the vertical axis represents the principal component 2. b Correlation between principal component 1/2 and 28 immune cell enrichment scores. c Immune landscape of the subgroups of IDH-wildtype GBM immune subtypes. Differences of 28 immune cells enrichment scores in the subgroups of IS3 (d) and IS4 (e). Immune landscape of samples from three extreme locations (f) and their prognostic status (g). -p ≥ 0.1, ·p < 0.1, *p < 0.05, **p < 0.01, ***p < 0.001. Figure S19. Functional immune genes modules in IDH-wildtype GBM. a Heatmap of four immune subtypes and seven gene modules in IDH-wildtype GBM. Genes are ordered based on the gene modules, and patients are arranged based on their immune subtypes. b Box plots of the expression patterns of seven gene modules of four immune subtypes in IDH-wildtype GBM. ****p < 0.0001. Table S1. Clinical characteristics of GBM patients in the TCGA cohort, REMBRANDT cohort and PD-1 inhibitor cohort. Table S4. IGP was estimated for each immune subtype in the validation cohort. Table S5. Functional enrichment analysis of gene modules

Additional file 2 of Tumor antigens and immune subtypes of glioblastoma: the fundamentals of mRNA vaccine and individualized immunotherapy development

Additional file 2: Table S2. The clinical information of TCGA cohort. Table S3. Immune-related genes. Table S6. Differentially expressed genes between responders and non-responders in pre-anti-PD-1 treatment samples. Table S7. Differentially expressed genes between responders and non-responders in post-anti-PD-1 treatment samples

Additional file 1: of TaNBP1, a guanine nucleotide-binding subunit gene of wheat, is essential in the regulation of N starvation adaptation via modulating N acquisition and ROS homeostasis

Table S1. PCR primers used in this study. Figure S1. The full length cDNA of TaNBP1 and the corresponding translated amino acids. The start codon ATG and the termination codon TAG of TaNBP1 are labeled by red background. Seven conserved WD40 repeat domains (I to VII) consisting of a sevenfold β-propeller in TaNBP1 are highlighted by blue background. Figure S2. Phylogenetic relations between TaNBP1 and its homologous genes from various plant species. Figure S3. Target gene transcripts in lines overexpressing TaNBP1 and NtNRT2.2 a, TaNBP1 transcripts in transgenic lines; b, NtNRT2.2 transcripts in transgenic lines. WT, wild type. Line 1 to Line 7, independent transgenic lines with TaNBP1 overexpression. NtNRT2.2–1 to NtNRT2.2–6, independent lines with NtNRT2.2 overexpression. In a, TaNBP1 expression levels in transgenic lines are normalized by the constitutive Tatubulin transcripts. In b, NtNRT2.2 expression levels in transgenic lines are normalized by the constitutive Nttubulin transcripts. Internal standard reference genes are set an expression level of 1. Figure S4. Target gene transcripts in lines overexpressing differential AE genes a, NtSOD1 transcripts in transgenic lines; b, NtSOD2 transcripts in transgenic lines; c, NtCAT1 transcripts in transgenic lines; WT, wild type. Expression levels of the AE genes in transgenic lines are normalized by the constitutive Nttubulin transcripts whose expression level is set as 1. (DOC 162 kb

White Light-Emitting Diodes Based on Ultrasmall CdSe Nanocrystal Electroluminescence

We report white light-emitting diodes fabricated with ultrasmall CdSe nanocrystals, which demonstrate electroluminescence from a size of nanocrystals (<2 nm) previously thought to be unattainable. These LEDs have excellent color characteristics, defined by their pure white CIE color coordinates (0.333, 0.333), correlated color temperatures of 5461−6007 K, and color rendering indexes as high as 96.6. The effect of high voltage on the trap states responsible for the white emission is also described

Targeted delivery by pH-responsive mPEG-S-PBLG micelles significantly enhances the anti-tumor efficacy of doxorubicin with reduced cardiotoxicity

Stimuli-responsive nanotherapeutics hold great promise in precision oncology. In this study, a facile strategy was used to develop a new class of pH-responsive micelles, which contain methoxy polyethylene glycol (mPEG) and poly(carbobenzoxy-l-glutamic acid, BLG) as amphiphilic copolymer, and β-thiopropionate as acid-labile linkage. The mPEG-S-PBLG copolymer was synthesized through one-step ring-opening polymerization (ROP) and thiol-ene click reaction, and was able to efficiently encapsulate doxorubicin (DOX) to form micelles. The physicochemical characteristics, cellular uptake, tumor targeting, and anti-tumor efficacy of DOX-loaded micelles were investigated. DOX-loaded micelles were stable under physiological conditions and disintegrated under acidic conditions. DOX-loaded micelles can be internalized into cancer cells and release drugs in response to low pH in endosomes/lysosomes, resulting in cell death. Furthermore, the micellar formulation significantly prolonged the blood circulation, reduced the cardiac distribution, and selectively delivered more drugs to tumor tissue. Finally, compared with free DOX, DOX-loaded micelles significantly improved the anti-tumor efficacy and reduced systemic and cardiac toxicity in two different tumor xenograft models. These results suggest that mPEG-S-PBLG micelles have translational potential in the precise delivery of anti-cancer drugs.</p

Spatial Localization of Excitons and Charge Carriers in Hybrid Perovskite Thin Films

The fundamental photophysics underlying the remarkably high-power conversion efficiency of organic–inorganic hybrid perovskite-based solar cells has been increasingly studied using complementary spectroscopic techniques. However, the spatially heterogeneous polycrystalline morphology of the photoactive layers owing to the presence of distinct crystalline grains has been generally neglected in optical measurements; therefore, the reported results are typically averaged over hundreds or even thousands of such grains. Here we apply femtosecond transient absorption microscopy to spatially and temporally probe ultrafast electronic excited-state dynamics in pristine methylammonium lead tri-iodide (CH₃NH₃PbI₃) thin films and composite structures. We found that the electronic excited-state relaxation kinetics are extremely sensitive to the sample location probed, which was manifested by position-dependent decay time scales and transient signals. Analysis of transient absorption kinetics acquired at distinct spatial positions enabled us to identify contributions of excitons and free charge carriers