Energy and performance trade-off optimization in heterogeneous computing via reinforcement learning

This paper suggests an optimisation approach in heterogeneous computing systems to balance energy power consumption and efficiency. The work proposes a power measurement utility for a reinforcement learning (PMU-RL) algorithm to dynamically adjust the resource utilisation of heterogeneous platforms in order to minimise power consumption. A reinforcement learning(RL) technique is applied to analyse and optimise the resource utilisation of field programmable gate array (FPGA) control state capabilities, which is built for a simulation environment with aXilinx ZYNQ multi-processor systems-on-chip (MPSoC) board. In this study, the balance operation mode for improving power consumption and performance is established to dynamically change the programmable logic (PL) end work state. It is based on an RL algorithm that can quickly discover the optimization effect of PL on different workloads to improve energy efficiency. The results demonstrate a substantial reduction of 18% in energy consumption without affecting the application’s performance. Thus, the proposed PMU-RL technique has the potential to be considered for other heterogeneous computing platforms

Eradication of Metastatic Renal Cell Carcinoma after Adenovirus-Encoded TNF-Related Apoptosis-Inducing Ligand (TRAIL)/CpG Immunotherapy

Despite evidence that antitumor immunity can be protective against renal cell carcinoma (RCC), few patients respond objectively to immunotherapy and the disease is fatal once metastases develop. We asked to what extent combinatorial immunotherapy with Adenovirus-encoded murine TNF-related apoptosis-inducing ligand (Ad5mTRAIL) plus CpG oligonucleotide, given at the primary tumor site, would prove efficacious against metastatic murine RCC. To quantitate primary renal and metastatic tumor growth in mice, we developed a luciferase-expressing Renca cell line, and monitored tumor burdens via bioluminescent imaging. Orthotopic tumor challenge gave rise to aggressive primary tumors and lung metastases that were detectable by day 7. Intra-renal administration of Ad5mTRAIL+CpG on day 7 led to an influx of effector phenotype CD4 and CD8 T cells into the kidney by day 12 and regression of established primary renal tumors. Intra-renal immunotherapy also led to systemic immune responses characterized by splenomegaly, elevated serum IgG levels, increased CD4 and CD8 T cell infiltration into the lungs, and elimination of metastatic lung tumors. Tumor regression was primarily dependent upon CD8 T cells and resulted in prolonged survival of treated mice. Thus, local administration of Ad5mTRAIL+CpG at the primary tumor site can initiate CD8-dependent systemic immunity that is sufficient to cause regression of metastatic lung tumors. A similar approach may prove beneficial for patients with metastatic RCC

Compressive sensing: From "Compressing while Sampling" to "Compressing and Securing while Sampling".

Published versio

Compressive sensing scalp EEG signals: implementations and practical performance.

Accepted versio