PowerFusion: A Tensor Compiler with Explicit Data Movement Description and Instruction-level Graph IR

Deep neural networks (DNNs) are of critical use in different domains. To accelerate DNN computation, tensor compilers are proposed to generate efficient code on different domain-specific accelerators. Existing tensor compilers mainly focus on optimizing computation efficiency. However, memory access is becoming a key performance bottleneck because the computational performance of accelerators is increasing much faster than memory performance. The lack of direct description of memory access and data dependence in current tensor compilers' intermediate representation (IR) brings significant challenges to generate memory-efficient code. In this paper, we propose IntelliGen, a tensor compiler that can generate high-performance code for memory-intensive operators by considering both computation and data movement optimizations. IntelliGen represent a DNN program using GIR, which includes primitives indicating its computation, data movement, and parallel strategies. This information will be further composed as an instruction-level dataflow graph to perform holistic optimizations by searching different memory access patterns and computation operations, and generating memory-efficient code on different hardware. We evaluate IntelliGen on NVIDIA GPU, AMD GPU, and Cambricon MLU, showing speedup up to 1.97x, 2.93x, and 16.91x(1.28x, 1.23x, and 2.31x on average), respectively, compared to current most performant frameworks.Comment: 12 pages, 14 figure

Quadrupolar D–A–D diketopyrrolopyrrole-based small molecule for ternary blend polymer solar cells

A quadrupole diketopyrrolopyrrole (DPP)-based small molecule (DPP4T-Cz) was designed and synthesized to enhance absorption coefficient, and then employed as the third component to improve the light harvesting of polymer solar cells based on a blend of poly(3-hexylthiophene) (P3HT) and [6, 6]-phenyl-C61-butyric acid methyl ester (PCBM). Because of an enhanced absorption coefficient of more than 105 cm−1, the photon harvesting efficiency was improved effectively in the near infrared (near-IR) range by using only a small amount of DPP4T-Cz (3.4 wt%) into the P3HT:PCBM binary blend polymer solar cells. Interestingly, the photocurrent generation was also enhanced in the visible range by the long-range energy transfer from P3HT to DPP4T-Cz molecules. As a result, the short-circuit current density (JSC) and power conversion efficiency (PCE) of P3HT:PCBM:DPP4T-Cz ternary blend devices were enhanced by more than 30% compared to those of P3HT:PCBM binary control devices. These findings suggest that quadrupole DPP-based molecules are one of the effective light-harvesting materials for ternary blend polymer solar cells

Sliding Mode Control of DFIG Wind Turbines with a Fast Exponential Reaching Law

This paper proposes a novel sliding mode control (SMC) technique for doubly fed induction generators (DFIGs) based on the fast exponential reaching law (FERL). The proposed FERL-based SMC is capable of reducing to a large extent the chattering phenomena existing in the sliding stage. Meanwhile, the reaching stage is accelerated with the introduction of an adaptive gain. The proposed method is employed in a DFIG-based wind energy conversion system (WECS) for direct power control (DPC). The FERL-based DPC approach is tested with simulations conducted in Matlab/Simulink under the scenarios of unbalanced grid voltage, grid fault conditions and highly unstable wind speed accompanied by an experimental study. The simulations and experimental results reveal the better performance of the proposed control method in active/reactive power tracking and dc-link voltage maintenance

Adaptive Droop Gain-Based Event-Triggered Consensus Reactive Power Sharing in Microgrids

This paper proposes an adaptive droop gain-based consensus approach for reactive power sharing in microgrids (MGs) with the event triggered communication protocol (ETCP). A multi-agent system-based network is constructed to establish the communication with distributed generators (DGs) in MGs. An ETCP is proposed to reduce the communication among agents to save resources and improve system reliability, as the communication is only needed when the event triggered condition is fulfilled. A stability analysis is conducted to guarantee the existence of the equilibrium point and the freeness of the Zeno solution. Moreover, an adaptive droop gain is designed to reduce the impact of imbalanced feeder impedances. Four case studies are conducted to verify the effectiveness and performance of the proposed method. The simulation results show that the ETCP-based approach is capable of achieving power sharing consensus, communication reduction and shifting the information exchange mode based on the operation scenarios

Nonlinear Controllers Based on Exact Feedback Linearization for Series-Compensated DFIG-Based Wind Parks to Mitigate Sub-Synchronous Control Interaction

The increasing penetration of wind power in the grid has driven the integration of wind farms with power systems that are series-compensated to enhance power transfer capability and dynamic stability. This may lead to sub-synchronous control interaction (SSCI) problems in series-compensated doubly-fed induction generator (DFIG)-based wind farms. To mitigate SSCI, nonlinear controllers based on exact feedback linearization (EFL) are proposed in this paper. Before deriving the control laws, the exact feedback linearizability of the studied system is scrutinized. Frequency scanning analysis is employed to test the designed EFL controllers. Moreover, the performance of the EFL controllers is compared to that of classical proportional-integral (PI) controllers. A series-compensated 100 MW DFIG-based wind park is utilized to assess the performance of the designed controllers through the alleviation of sub-synchronous resonance. Analyses of the studied system reveal that the resistance is negative under sub-synchronous frequency conditions, whereas the reactance becomes negative at approximately 44 Hz. The designed EFL controllers effectively alleviate SSCI and result in positive reactance and resistance values within the whole sub-synchronous frequency range. The results from the frequency scanning method are also validated through the time domain simulation and the eigenvalue analysis

A new IRES-mediated truncated Cx32 isoform inhibits global mRNA translation to suppress glioblastoma

Glioblastoma (GBM) is the most lethal malignant primary brain tumor. Although multimodal therapy has been applied for GBM, the median survival time remains less than 16 months. Thus, better therapeutic targets in GBM are urgently needed. Herein, we first identified five new N-terminal-truncated Cx32 isoforms (GJB1–28k, GJB1–22k, GJB1–20k, GJB1–15k, and GJB1–13k) and further demonstrated that they were generated via cap-independent internal translation through internal ribosome entry sites (IRESs) in the coding sequence of GJB1 mRNA. Among these isoforms, GJB1–13k inhibited proliferation, promoted apoptosis, and limited cell cycle progression in GBM cells by inhibiting global mRNA translation. In vivo experiments further confirmed the antitumor activity of GJB1–13k against GBM cells. In addition, TSR3, a ribosomal maturation factor, was demonstrated to directly interact with GJB1–13k. Moreover, GBM cells with high TSR3 expression exhibited low sensitivity to GJB1–13k treatment, while GJB1–13k sensitivity was restored by TSR3 knockdown. Our work identifies a new IRES-mediated protein, GJB1–13k, and suggests that overexpression of GJB1–13k in GBM cells with low TSR3 expression or combined targeting of GJB1–13k and TSR3 in GBM cells with high TSR3 expression constitutes a potential therapeutic strategy for GBM

Single-Cell Transcriptome Identifies the Renal Cell Type Tropism of Human BK Polyomavirus

BK polyomavirus (BKPyV) infection is the main factor affecting the prognosis of kidney transplant recipients, as no antiviral agent is yet available. A better understanding of the renal-cell-type tropism of BKPyV can serve to develop new treatment strategies. In this study, the single-cell transcriptomic analysis demonstrated that the ranking of BKPyV tropism for the kidney was proximal tubule cells (PT), collecting duct cells (CD), and glomerular endothelial cells (GEC) according to the signature of renal cell type and immune microenvironment. In normal kidneys, we found that BKPyV infection-related transcription factors P65 and CEBPB were PT-specific transcription factors, and PT showed higher glycolysis/gluconeogenesis activities than CD and GEC. Furthermore, in the BKPyV-infected kidneys, the percentage of late viral transcripts in PT was significantly higher than in CD and GEC. In addition, PT had the smallest cell–cell interactions with immune cells compared to CD and GEC in both normal and BKPyV-infected kidneys. Subsequently, we indirectly demonstrated the ranking of BKPyV tropism via the clinical observation of sequential biopsies. Together, our results provided in-depth insights into the renal cell-type tropism of BKPyV in vivo at single-cell resolution and proposed a novel antiviral target