A comparison of variational and Markov chain Monte Carlo methods for inference in partially observed stochastic dynamic systems

In recent work we have developed a novel variational inference method for partially observed systems governed by stochastic differential equations. In this paper we provide a comparison of the Variational Gaussian Process Smoother with an exact solution computed using a Hybrid Monte Carlo approach to path sampling, applied to a stochastic double well potential model. It is demonstrated that the variational smoother provides us a very accurate estimate of mean path while conditional variance is slightly underestimated. We conclude with some remarks as to the advantages and disadvantages of the variational smoother. © 2008 Springer Science + Business Media LLC

In-Datacenter Performance Analysis of a Tensor Processing Unit

Many architects believe that major improvements in cost-energy-performance must now come from domain-specific hardware. This paper evaluates a custom ASIC---called a Tensor Processing Unit (TPU)---deployed in datacenters since 2015 that accelerates the inference phase of neural networks (NN). The heart of the TPU is a 65,536 8-bit MAC matrix multiply unit that offers a peak throughput of 92 TeraOps/second (TOPS) and a large (28 MiB) software-managed on-chip memory. The TPU's deterministic execution model is a better match to the 99th-percentile response-time requirement of our NN applications than are the time-varying optimizations of CPUs and GPUs (caches, out-of-order execution, multithreading, multiprocessing, prefetching, ...) that help average throughput more than guaranteed latency. The lack of such features helps explain why, despite having myriad MACs and a big memory, the TPU is relatively small and low power. We compare the TPU to a server-class Intel Haswell CPU and an Nvidia K80 GPU, which are contemporaries deployed in the same datacenters. Our workload, written in the high-level TensorFlow framework, uses production NN applications (MLPs, CNNs, and LSTMs) that represent 95% of our datacenters' NN inference demand. Despite low utilization for some applications, the TPU is on average about 15X - 30X faster than its contemporary GPU or CPU, with TOPS/Watt about 30X - 80X higher. Moreover, using the GPU's GDDR5 memory in the TPU would triple achieved TOPS and raise TOPS/Watt to nearly 70X the GPU and 200X the CPU.Comment: 17 pages, 11 figures, 8 tables. To appear at the 44th International Symposium on Computer Architecture (ISCA), Toronto, Canada, June 24-28, 201

Variants in ADRB1 and CYP2C9: Association with Response to Atenolol and Losartan in Marfan Syndrome

Objective: To test whether variants in ADRB1 and CYP2C9 genes identify subgroups of individuals with differential response to treatment for Marfan syndrome through analysis of data from a large, randomized trial. Study design: In a subset of 250 white, non-Hispanic participants with Marfan syndrome in a prior randomized trial of atenolol vs losartan, the common variants rs1801252 and rs1801253 in ADRB1 and rs1799853 and rs1057910 in CYP2C9 were analyzed. The primary outcome was baseline-adjusted annual rate of change in the maximum aortic root diameter z-score over 3 years, assessed using mixed effects models. Results: Among 122 atenolol-assigned participants, the 70 with rs1801253 CC genotype had greater rate of improvement in aortic root z-score compared with 52 participants with CG or GG genotypes (Time × Genotype interaction P = .005, mean annual z-score change ± SE -0.20 ± 0.03 vs -0.09 ± 0.03). Among participants with the CC genotype in both treatment arms, those assigned to atenolol had greater rate of improvement compared with the 71 of the 121 assigned to losartan (interaction P = .002; -0.20 ± 0.02 vs -0.07 ± 0.02; P < .001). There were no differences in atenolol response by rs1801252 genotype or in losartan response by CYP2C9 metabolizer status. Conclusions: In this exploratory study, ADRB1-rs1801253 was associated with atenolol response in children and young adults with Marfan syndrome. If these findings are confirmed in future studies, ADRB1 genotyping has the potential to guide therapy by identifying those who are likely to have greater therapeutic response to atenolol than losartan

Validation of Human Telomere Length Multi-Ancestry Meta-Analysis Association Signals Identifies POP5 and KBTBD6 as Human Telomere Length Regulation Genes

Genome-wide association studies (GWAS) have become well-powered to detect loci associated with telomere length. However, no prior work has validated genes nominated by GWAS to examine their role in telomere length regulation. We conducted a multi-ancestry meta-analysis of 211,369 individuals and identified five novel association signals. Enrichment analyses of chromatin state and cell-type heritability suggested that blood/immune cells are the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6 or POP5 and demonstrated that both lengthened telomeres. CRISPR/Cas9 deletion of the predicted causal regions in K562 blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5. Our results demonstrate the utility of telomere length GWAS in the identification of telomere length regulation mechanisms and validate KBTBD6 and POP5 as genes affecting telomere length regulation

Image-Based Lighting for Games

computer graphics, texture mapping, image-based rendering Image-based rendering techniques are used extensively in interactive electronic games. Most frequently image-based rendering appears in the form of texture mapping when a photograph or image is used to represent a complex object&apos;s appearance. Texture mapping has several significant limitations, the primary one being that only a single lighting condition is captured. If dynamic lighting is needed, texture mapping alone is insufficient. This report describes some existing techniques to solve this problem as well as a technique for image-based lighting developed at HP Labs. Our method, Polynomial Texture Mapping (PTM) uses biquadtatic polynomials at every texel to reconstruct surface appearances under varying lighting conditions. Unlike previous methods, PTMs can capture complex illumination effects such as self-shadowing and interreflections. Our method can be efficiently implemented on programmable graphics hardware which is common to most current and future electronic gaming platforms

Polynomial texture maps

graphics hardware, illumination, image processing, image-based rendering, reflectance &amp; shading models, texture mapping In this paper we present a new form of texture mapping that produces increased photorealism. Coefficients of a biquadratic polynomial are stored per texel, and used to reconstruct the surface color under varying lighting conditions. Like bump mapping, this allows the perception of surface deformations. However, our method is image based, and photographs of a surface under varying lighting conditions can be used to construct these maps. Unlike bump maps, these Polynomial Texture Maps (PTMs) also capture variations due to surface self-shadowing and interreflections, which enhance realism. Surface colors can be efficiently reconstructed from polynomial coefficients and light directions with minimal fixed-point hardware. We have also found PTMs useful for producing a number of other effects such as anisotropic and Fresnel shading models and variable depth of focus. Lastly, we present several reflectance function transformations that act as contrast enhancement operators. We have found these particularly useful in the study of ancient archeological clay and stone writings

© Copyright Hewlett-Packard Company 2003 Synthesis of Reflectance Function Textures from Examples

texture synthesis, reflectance models, computer graphics We extend the machinery of existing texture synthesis methods to handle texture images where each pixel contains not only RGB values, but reflectance functions. Like conventional texture synthesis methods, we can use photographs of surface textures as examples to base synthesis from. However multiple photographs of the same surface are used to characterize the surface across lighting variation, and synthesis is based on these source images. Our approach performs synthesis directly in the space of reflectance functions and does not require any intermediate 3D reconstruction of the target surface. The resulting synthetic reflectance textures can be rendered in real-time with continuous control of lighting direction