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CuPy
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU. CuPy supports NVIDIA CUDA GPU platform, and AMD ROCm GPU platform starting in v9.0. CuPy has been initially developed as a backend of Chainer deep learning framework, and later established as an independent project in 2017. CuPy is a part of the NumPy ecosystem array libraries and is widely adopted to utilize GPU with Python, especially in high-performance computing environments such as Summit, Perlmutter, Eluer, and ABCI. CuPy is a NumFOCUS affiliated project. Features CuPy implements NumPy/SciPy-compatible APIs, as well as features to write user-defined GPU kernels or access low-level APIs. NumPy-compatible APIs The same ...
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CUDA
CUDA (or Compute Unified Device Architecture) is a parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for general purpose processing, an approach called general-purpose computing on GPUs (GPGPU). CUDA is a software layer that gives direct access to the GPU's virtual instruction set and parallel computational elements, for the execution of compute kernels. CUDA is designed to work with programming languages such as C, C++, and Fortran. This accessibility makes it easier for specialists in parallel programming to use GPU resources, in contrast to prior APIs like Direct3D and OpenGL, which required advanced skills in graphics programming. CUDA-powered GPUs also support programming frameworks such as OpenMP, OpenACC and OpenCL; and HIP by compiling such code to CUDA. CUDA was created by Nvidia. When it was first introduced, the name was an acronym for Compute Unified Device Architectur ...
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Chainer
Chainer is an open source deep learning framework written purely in Python on top of NumPy and CuPy Python libraries. The development is led by Japanese venture company Preferred Networks in partnership with IBM, Intel, Microsoft, and Nvidia. Chainer is notable for its early adoption of " define-by-run" scheme, as well as its performance on large scale systems. The first version was released in June 2015 and has gained large popularity in Japan since then. Furthermore, in 2017, it was listed by KDnuggets in top 10 open source machine learning Python projects. In December 2019, Preferred Networks announced the transition of its development effort from Chainer to PyTorch and it will only provide maintenance patches after releasing v7. Define-by-run Chainer was the first deep learning framework to introduce the define-by-run approach. The traditional procedure to train a network was in two phases: define the fixed connections between mathematical operations (such as matrix multip ...
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ROCm
ROCm is an Advanced Micro Devices (AMD) software stack for graphics processing unit (GPU) programming. ROCm spans several domains: general-purpose computing on graphics processing units (GPGPU), high performance computing (HPC), heterogeneous computing. It offers several programming models: HIP ( GPU-kernel-based programming), OpenMP/ Message Passing Interface (MPI) ( directive-based programming), OpenCL. ROCm is free, libre and open-source software (except the GPU firmware blobs), it is distributed under various licenses. Background The first GPGPU software stack from ATI/AMD was Close to Metal, which became Stream. ROCm was launched around 2016 with the Boltzmann Initiative. ROCm stack builds upon previous AMD GPU stacks, some tools trace back to GPUOpen, others to the Heterogeneous System Architecture (HSA). Heterogeneous System Architecture HSA was aimed at producing a middle-level, hardware-agnostic intermediate representation, that could be JIT-compiled to the ev ...
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GitHub
GitHub, Inc. () is an Internet hosting service for software development and version control using Git. It provides the distributed version control of Git plus access control, bug tracking, software feature requests, task management, continuous integration, and wikis for every project. Headquartered in California, it has been a subsidiary of Microsoft since 2018. It is commonly used to host open source software development projects. As of June 2022, GitHub reported having over 83 million developers and more than 200 million repositories, including at least 28 million public repositories. It is the largest source code host . History GitHub.com Development of the GitHub.com platform began on October 19, 2007. The site was launched in April 2008 by Tom Preston-Werner, Chris Wanstrath, P. J. Hyett and Scott Chacon after it had been made available for a few months prior as a beta release. GitHub has an annual keynote called GitHub Universe. Organizational ...
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Array Data Type
In computer science, array is a data type that represents a collection of ''elements'' (value (computer science), values or variable (computer science), variables), each selected by one or more indices (identifying keys) that can be computed at Run time (program lifecycle phase), run time during program execution. Such a collection is usually called an array variable or array value.Robert W. Sebesta (2001) ''Concepts of Programming Languages''. Addison-Wesley. 4th edition (1998), 5th edition (2001), By analogy with the mathematical concepts vector (mathematics), vector and matrix (mathematics), matrix, array types with one and two indices are often called vector type and matrix type, respectively. More generally, a multidimensional array type can be called a tensor type, by anology with the physical concept, tensor. Language support for array types may include certain built-in type, built-in array data types, some syntactic constructions (''array type constructors'') that the p ...
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AI Bridging Cloud Infrastructure
AI Bridging Cloud Infrastructure (ABCI) is a planned supercomputer being built at the University of Tokyo for use in artificial intelligence, machine learning, and deep learning. It is being built by Japan's National Institute of Advanced Industrial Science and Technology. ABCI is expected to be completed in first quarter 2018 with a planned performance of 130 petaFLOPS. Power consumption is targeting 3 megawatts, and a planned power usage effectiveness of 1.1. If performance meets expectations, ABCI would be the second most powerful supercomputer built, surpassing the current leader Sunway TaihuLight's 93 petaflops. But still behind the Summit (supercomputer). History In November 2014 it was announced that a 160 petaFLOPS system will be built for ( – ), with construction to begin in 2017. In October 2017 Fujitsu got the contract to build a 37 petaFLOPS system for . Design The design of the ABCI is to be focused on low precision floating point, big data, and artifici ...
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National Institute Of Advanced Industrial Science And Technology
The , or AIST, is a Japanese research facility headquartered in Tokyo, and most of the workforce is located in Tsukuba Science City, Ibaraki, and in several cities throughout Japan. The institute is managed to integrate scientific and engineering knowledge to address socio-economic needs. It became a newly designed legal body of Independent Administrative Institution in 2001, remaining under the Ministry of Economy, Trade and Industry. History In its present form AIST was established in 2001. However, its predecessor institutes have been operating since 1882. In 2015, it is running more than 40 researching institutes and several branches over Japan including International Metrology Cooperation Office. Three missions of AIST # Advanced Research by exploring broad spectra of research fields and integrating multidisciplinary subjects to promote innovation in versatile fields that strengthen the competitiveness of Japanese industries in the world market and create new industries. ...
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Fast Fourier Transform
A fast Fourier transform (FFT) is an algorithm that computes the discrete Fourier transform (DFT) of a sequence, or its inverse (IDFT). Fourier analysis converts a signal from its original domain (often time or space) to a representation in the frequency domain and vice versa. The DFT is obtained by decomposing a sequence of values into components of different frequencies. This operation is useful in many fields, but computing it directly from the definition is often too slow to be practical. An FFT rapidly computes such transformations by factorizing the DFT matrix into a product of sparse (mostly zero) factors. As a result, it manages to reduce the complexity of computing the DFT from O\left(N^2\right), which arises if one simply applies the definition of DFT, to O(N \log N), where N is the data size. The difference in speed can be enormous, especially for long data sets where ''N'' may be in the thousands or millions. In the presence of round-off error, many FFT algorithm ...
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Linear Algebra
Linear algebra is the branch of mathematics concerning linear equations such as: :a_1x_1+\cdots +a_nx_n=b, linear maps such as: :(x_1, \ldots, x_n) \mapsto a_1x_1+\cdots +a_nx_n, and their representations in vector spaces and through matrices. Linear algebra is central to almost all areas of mathematics. For instance, linear algebra is fundamental in modern presentations of geometry, including for defining basic objects such as lines, planes and rotations. Also, functional analysis, a branch of mathematical analysis, may be viewed as the application of linear algebra to spaces of functions. Linear algebra is also used in most sciences and fields of engineering, because it allows modeling many natural phenomena, and computing efficiently with such models. For nonlinear systems, which cannot be modeled with linear algebra, it is often used for dealing with first-order approximations, using the fact that the differential of a multivariate function at a point is the linear ma ...
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Brutus Cluster
Brutus is the central high-performance cluster of ETH Zurich. It was introduced to the public in May 2008. A new computing cluster called EULER has been announced and opened to the public in May 2014. Processors Brutus is a heterogeneous system containing 11 different kinds of compute nodes: ;Standard nodes * 120 nodes with four 12-core AMD Opteron 6174 CPUs and 64 GB of RAM'' (5760 cores)'' * 24 nodes with two 12-core AMD Opteron 6174 CPUs and 32 GB of RAM'' (576 cores)'' * 410 nodes with four quad-core AMD Opteron 8380 CPUs and 32 GB of RAM'' (6560 cores)'' * 80 nodes with four quad-core AMD Opteron 8384 CPUs and 32 GB of RAM'' (1280 cores)'' ;Large-memory (fat) nodes * 6 nodes with four 8-core Intel Xeon E7-8837 CPUs and 1024 GB of RAM'' (192 cores)'' ''— NEW! * 80 nodes with four 12-core AMD Opteron 6174 CPUs and 256 GB of RAM'' (3840 cores)'' * 10 nodes with four quad-core AMD Opteron 8380 CPUs and 128 GB of RAM'' (160 cores)'' ;GPU nodes * 18 nodes with two 12-co ...
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Random Number Generation
Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated. This means that the particular outcome sequence will contain some patterns detectable in hindsight but unpredictable to foresight. True random number generators can be '' hardware random-number generators'' (HRNGS) that generate random numbers, wherein each generation is a function of the current value of a physical environment's attribute that is constantly changing in a manner that is practically impossible to model. This would be in contrast to so-called "random number generations" done by ''pseudorandom number generators'' (PRNGs) that generate numbers that only look random but are in fact pre-determined—these generations can be reproduced simply by knowing the state of the PRNG. Various applications of randomness have led to the development of several different metho ...
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