Abstract: A fully-connected neural network may be configured for execution by a processor as a fully-fused neural network by limiting slow global memory accesses to reading and writing inputs to and outputs from the fully-connected neural network. The computational cost of fully-connected neural networks scale quadratically with its width, whereas its memory traffic scales linearly. Modern graphics processing units typically have much greater computational throughput compared with memory bandwidth, so that for narrow, fully-connected neural networks, the linear memory traffic is the bottleneck. The key to improving performance of the fully-connected neural network is to minimize traffic to slow “global” memory (off-chip memory and high-level caches) and to fully utilize fast on-chip memory (low-level caches, “shared” memory, and registers), which is achieved by the fully-fused approach.

Abstract: The present invention relates to an improved method for determining the amount of FVIII inhibitors in a patient sample, comprising the provision of a patient plasma sample, a normal pool plasma samples, and a control plasma sample which is FVIII/VWF deficient, inactivating all clotting factors present in the samples, addition of recombinant FVIII (rFVIII) to the control plasma sample, combination of the patient plasma sample with the control plasma sample with rFVIII to obtain a test mixture, and of the normal plasma pool sample with the control plasma sample with rFVIII to obtain a control mixture, incubation of the test mixture and the control mixture for less than 30 minutes, and analyzing the mixtures for residual rFVIII activity in the absence of VWF.

Abstract: In photorealistic image synthesis by light transport simulation, the colors of each pixel are an integral of a high-dimensional function. However, the functions to integrate contain discontinuities that cannot be predicted efficiently. In practice, the pixel colors are estimated by using Monte Carlo and quasi-Monte Carlo methods to sample light transport paths that connect light sources and cameras and summing up the contributions to evaluate an integral. Because of the sampling, images appear noisy when the number of samples is insufficient. A low discrepancy sequence provides sample locations and these sample locations can be enumerated (assigned or distributed to pixels) according to a space-filling curve superimposed on a pixel grid. Correlations of such combinations of space-filling curves and low discrepancy sequences are analyzed, and the presented algorithms reduce correlations, are deterministic, and may be executed for each pixel in parallel.

Abstract: A fully-connected neural network may be configured for execution by a processor as a fully-fused neural network by limiting slow global memory accesses to reading and writing inputs to and outputs from the fully-connected neural network. The computational cost of fully-connected neural networks scale quadratically with its width, whereas its memory traffic scales linearly. Modern graphics processing units typically have much greater computational throughput compared with memory bandwidth, so that for narrow, fully-connected neural networks, the linear memory traffic is the bottleneck. The key to improving performance of the fully-connected neural network is to minimize traffic to slow “global” memory (off-chip memory and high-level caches) and to fully utilize fast on-chip memory (low-level caches, “shared” memory, and registers), which is achieved by the fully-fused approach.

Abstract: A fully-connected neural network may be configured for execution by a processor as a fully-fused neural network by limiting slow global memory accesses to reading and writing inputs to and outputs from the fully-connected neural network. The computational cost of fully-connected neural networks scale quadratically with its width, whereas its memory traffic scales linearly. Modern graphics processing units typically have much greater computational throughput compared with memory bandwidth, so that for narrow, fully-connected neural networks, the linear memory traffic is the bottleneck. The key to improving performance of the fully-connected neural network is to minimize traffic to slow “global” memory (off-chip memory and high-level caches) and to fully utilize fast on-chip memory (low-level caches, “shared” memory, and registers), which is achieved by the fully-fused approach.

Abstract: Neural network performance is improved in terms of training speed and/or accuracy by encoding (mapping) inputs to the neural network into a higher dimensional space via a hash function. The input comprises coordinates used to identify a point within a d-dimensional space (e.g., 3D space). The point is quantized and a set of vertex coordinates corresponding to the point are input to a hash function. For example, for d=3, space may be partitioned into axis-aligned voxels of identical size and vertex coordinates of a voxel containing the point are input to the hash function to produce a set of encoded coordinates. The set of encoded coordinates is used to lookup D-dimensional feature vectors in a table of size T that have been learned. The learned feature vectors are filtered (e.g., linearly interpolated, etc.) based on the coordinates of the point to compute a feature vector corresponding to the point.

Abstract: A fully-connected neural network may be configured for execution by a processor as a fully-fused neural network by limiting slow global memory accesses to reading and writing inputs to and outputs from the fully-connected neural network. The computational cost of fully-connected neural networks scale quadratically with its width, whereas its memory traffic scales linearly. Modern graphics processing units typically have much greater computational throughput compared with memory bandwidth, so that for narrow, fully-connected neural networks, the linear memory traffic is the bottleneck. The key to improving performance of the fully-connected neural network is to minimize traffic to slow “global” memory (off-chip memory and high-level caches) and to fully utilize fast on-chip memory (low-level caches, “shared” memory, and registers), which is achieved by the fully-fused approach.

Abstract: An apparatus, computer readable medium, and method are disclosed for decompressing compressed geometric data stored in a lossless compression format. The compressed geometric data resides within a compression block sized according to a system cache line. An indirection technique maps a global identifier value in a linear identifier space to corresponding variable rate compressed data. The apparatus may include decompression circuitry within a graphics processing unit configured to perform ray-tracing.

Abstract: A method, computer readable medium, and system are disclosed for performing tree traversal with backtracking in constant time. The method includes the steps of traversing a tree, maintaining a bit trail variable and a current key variable during the traversing, where the bit trail variable includes a first plurality of bits indicating tree levels on which a node has been postponed along a path from the root of the tree during the traversing, and the current key variable includes a second plurality of bits indicating a number of a current node within the tree, and performing backtracking within the tree during the traversing, utilizing the bit trail variable and the current key variable.

Abstract: A method, computer readable medium, and system are disclosed for reducing noise during a rendering of a scene by sharing information that is spatially close through path space filtering. A vertex of a light transport path is selected, and one or more features of the selected vertex are quantized. A first hash is calculated based on the one or more quantized features of the selected vertex, and a collision resolution is performed within a hash table. A contribution of the light transport path at the selected vertex is accumulated to the hash table, and a counter is incremented in response to adding the contribution of the light transport path at the selected vertex to the hash table. An average contribution of the light transport path is then calculated, utilizing the counter.

Abstract: The present invention relates to an antibody which has specific reactivity (affinity) to an antigenic determinant site produced by ADAMTS-13 or a peptide having the amino acid sequence represented by SEQ ID NO: 1 given in the sequence listing, a method for producing the same; and a use thereof in a rapid assay.

Abstract: An apparatus, computer readable medium, and method are disclosed for decompressing compressed geometric data stored in a lossless compression format. The compressed geometric data resides within a compression block sized according to a system cache line. An indirection technique maps a global identifier value in a linear identifier space to corresponding variable rate compressed data. The apparatus may include decompression circuitry within a graphics processing unit configured to perform ray-tracing.

Abstract: A method, a computer program, and a production renderer for accelerating a rendering process of an image are provided. In one embodiment, the method includes intercepting a first invocation of a function from a custom shader during a rendering process of an image, computing a result of the function employing a processor, and returning the result to the custom shader in response to a second invocation of the function during the rendering process.

Abstract: A method, computer readable medium, and system are disclosed for reducing noise during a rendering of a scene by sharing information that is spatially close through path space filtering. A vertex of a light transport path is selected, and one or more features of the selected vertex are quantized. A first hash is calculated based on the one or more quantized features of the selected vertex, and a collision resolution is performed within a hash table. A contribution of the light transport path at the selected vertex is accumulated to the hash table, and a counter is incremented in response to adding the contribution of the light transport path at the selected vertex to the hash table. An average contribution of the light transport path is then calculated, utilizing the counter.

Abstract: A method and renderer for a progressive computation of a light transport simulation are provided. The method includes the steps of employing a low discrepancy sequence of samples; and scrambling an index of the low discrepancy sequence independently per region using a hash value based on coordinates of a respective region, wherein for each set of a power-of-two number of the samples, the scrambling is a permutation.

Abstract: A system, method, and computer program product are provided for performing path space filtering. In use, a set of light transport paths associated with a scene is sampled. Additionally, a plurality of vertices associated with the sampled set of light transport paths is selected, where each selected vertex has an associated throughput and light contribution. Further, an averaged light contribution of each of the selected plurality of vertices is determined, utilizing one or more weights. Further still, the averaged light contribution of each of the selected plurality of vertices is combined after multiplying the averaged light contribution of each of the selected vertices by the associated throughput of the vertex.

Abstract: A method, a computer program, and a production renderer for accelerating a rendering process of an image are provided. In one embodiment, the method includes intercepting a first invocation of a function from a custom shader during a rendering process of an image, computing a result of the function employing a processor, and returning the result to the custom shader in response to a second invocation of the function during the rendering process.

Abstract: A method, computer readable medium, and system are disclosed for performing tree traversal with backtracking in constant time. The method includes the steps of traversing a tree, maintaining a bit trail variable and a current key variable during the traversing, where the bit trail variable includes a first plurality of bits indicating tree levels on which a node has been postponed along a path from the root of the tree during the traversing, and the current key variable includes a second plurality of bits indicating a number of a current node within the tree, and performing backtracking within the tree during the traversing, utilizing the bit trail variable and the current key variable.

Abstract: A method and renderer for a progressive computation of a light transport simulation are provided. The method includes the steps of employing a low discrepancy sequence of samples; and scrambling an index of the low discrepancy sequence independently per region using a hash value based on coordinates of a respective region, wherein for each set of a power-of-two number of the samples, the scrambling is a permutation.

Abstract: A system, method, and computer program product are provided for determining a quantity of light received by an element of a scene. In use, a quantity of light received by a first element of the scene is determined by averaging a quantity of light received by elements of the scene that are associated with a selected set of light paths.