Search Results for "compute"
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Showing 25 open source projects for "compute"
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Karpenter
Kubernetes Node Autoscaling: built for flexibility, and performance
Karpenter simplifies Kubernetes infrastructure with the right nodes at the right time. Karpenter automatically launches just the right compute resources to handle your cluster's applications. It is designed to let you take full advantage of the cloud with fast and simple compute provisioning for Kubernetes clusters. Karpenter responds quickly and automatically to changes in application load, scheduling, and resource requirements, placing new workloads on a variety of available compute resource capacities. ... -
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VulkanSceneGraph
Vulkan & C++17 based Scene Graph Project
VulkanSceneGraph (VSG), is a modern, cross-platform, high-performance scene graph library built upon Vulkan graphics/compute API. The software is written in C++17 and follows the CppCoreGuidelines and FOSS Best Practices. The source code is published under the MIT License, with the exception of vulkan.h, used for Vulkan extensions, which is under Apache License 2.0. This repository contains C++ headers and source and CMake build scripts to build the libvsg library. -
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AWS ParallelCluster Node
Python package installed on the Amazon EC2 instances
...AWS ParallelCluster is an AWS-supported Open Source cluster management tool that makes it easy for you to deploy and manage High-Performance Computing (HPC) clusters in the AWS cloud. Built on the Open Source CfnCluster project, AWS ParallelCluster enables you to quickly build an HPC compute environment in AWS. It automatically sets up the required compute resources and a shared filesystem and offers a variety of batch schedulers such as AWS Batch and Slurm. AWS ParallelCluster facilitates both quick start proof of concepts (POCs) and production deployments. You can build higher-level workflows, such as a Genomics portal that automates the entire DNA sequencing workflow, on top of AWS ParallelCluster. -
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Cloud Storage FUSE
A user-space file system for interacting with Google Cloud Storage
...It supports performance optimizations like file caching, which stores frequently accessed data on local storage to significantly improve throughput and reduce latency. The system integrates with cloud-native environments such as Kubernetes and can be used in distributed architectures where multiple compute nodes access shared datasets. -
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EPLB
Expert Parallelism Load Balancer
...The logic is implemented in eplb.py and supports predicting placements given estimated expert usage weights. EPLB aims to reduce hot-spotting and ensure more uniform usage of compute resources in large MoE deployments. -
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Alluxio
Open Source Data Orchestration for the Cloud
...It bridges the gap between computation frameworks and storage systems, bringing data from the storage tier closer to the data driven applications. This enables applications to connect to numerous storage systems through a common interface. It makes data local, more accessible and as elastic as compute. -
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UNICORE
UNiform Interface to COmputing and data REsources
UNICORE is a software suite for building federated systems, providing secure and seamless access to heterogeneous resource such as compute clusters and file systems. UNICORE deals with authentication, user mapping and authorization, and provides a comprehensive set of RESTful APIs for HPC access and workflows. Contributors: visit https://github.com/UNICORE-EU -
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...You can run Pelican on a single multiple core machine to use all cores to solve a problem, or you can network multiple computers together to make a cluster. The frontend node (either a real computer or a virtual machine) boots from the image. The compute nodes boot by PXE, using the frontend node as the server. All of the nodes of the cluster get their filesystems from the same image, so it is guaranteed that all nodes run the the same software. Packages can be added to all nodes using apt-get, thanks to aufs. The bootable image is created by running a single script, which takes advantage of the Debian Live infrastructure.
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UniSIMD-assembler
SIMD macro assembler unified for ARM, MIPS, PPC and x86
UniSIMD assembler is a high-level C/C++ macro assembler framework unified across ARM, MIPS, POWER and x86 architectures. It establishes a subset of both BASE and SIMD instruction sets with clearly defined common API, so that application logic can be written and maintained in one place without code replication. The assembler itself isn't a separate tool, but rather a collection of C/C++ header files, which applications need to include directly in order to use. At present, Intel... -
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GPCS4
A work-in-progress PlayStation 4 emulator
...A project done for fun, and for technical research. The only reason I have started this project is for learning 3D graphics. It's not intended to become a serious application. Support simple compute shader, compute ring, cube maps. For more details you could join our discord server to contact me, or if you are used to Tencent QQ/TIM, just join our group. There you can get more resources which are useful for contributing. To run or develop GPCS4, a CPU supporting AVX instruction set as well as a graphics card supporting Vulkan 1.3 are required. -
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dispy
Distributed and Parallel Computing with/for Python.
dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing. -
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FreeRTOS AWS Reference Integrations
IoT operating system for microcontrollers.
...A microcontroller contains a simple, resource-constrained processor that can be found in many devices, including appliances, sensors, fitness trackers, industrial automation, and automobiles. Many of these small devices can benefit from connecting to the cloud or locally to other devices, but have limited compute power and memory capacity. -
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BlockSparse
Efficient GPU kernels for block-sparse matrix multiplication
The blocksparse repository provides efficient GPU kernels (TensorFlow custom ops) for block-sparse matrix multiplication and convolution operations. The idea is to exploit block-level sparsity — i.e. treat matrices or weight tensors as composed of blocks, many of which may be zero or unused — to save compute and memory when sparsity patterns are structured. This is particularly useful in models like Sparse Transformers, where attention matrices or intermediate layers may adopt block-sparse patterns to scale better. The repo implements both blocksparse and blockwise convolution/transpose-convolution primitives, with support for preparing, executing, and verifying those ops on NVIDIA GPUs. ... -
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RainforestCluster
Dynamically manage Amazon EC2 clusters
RainforestCluster is an Amazon EC2 python program that manages and load-balances dynamic clusters to allow for maximum workflow flexibility and speed at minimal cost. It enables one to quickly and cheaply create dynamic compute clusters in the cloud, which can then run computational pipelines generically. It is also able to optimize the use of spot instances - idle computers in Amazon's cloud that are available at drastically reduced cost (5x-10x cheaper) - but can be terminated at any moment if capacity drops or the bid price rises. It also provides pre-installed features such as GlusterFS distributed filesystems, ThunderstormDistributor queuing system, RAID 0 /scratch, password-less ssh, and automatic cluster management, for ease of use and maximum processing speed for computational tools. ... -
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Mpaxs
Transparent Local and Remote Parallelization for Java
Mpaxs provides a simple abstraction for executing Callables and Runnables either locally within the same Virtual Machine, on the same host via RMI, or on remote machines, also via RMI. It supports launching of new compute hosts via an extensible API, currently featuring local compute host launching and grid compute host launching using the DRMAA API. -
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Rosefinch is a web file manager. Cut, copy, paste, rename and delete and make new folder in browser just like use other file managers on your compute. Also, Rosefinch provides download, upload and search feature. Rosefinch can be an alternative of Ap
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birgHPCC
Rapid CUDA Cluster Deployment
...While retaining the major functions of the original birgHPC, including automated computing cluster conversion and auto slots detection, the new version (birgHPCC) is capable of creating and configuring a compute unified device architecture (CUDA) computing cluster, hence the extra “C” in the name. In addition to the increase in image size (less than 2 gigabytes) and a new Linux base (previously Debian, now Ubuntu), CUDA-capable bioinformatics software programs, such as NAMD, HOOMD-blue, VMD, GPU-HMMER and GPU-BLAST, are pre-installed in birgHPCC, along with the CUDA driver, libraries and software development kit (SDK). ... -
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hpc-sjm
Simple Job Manager
SJM is a tool for managing jobs running on a compute cluster with a job scheduler such as Sun Grid Engine or Platform LSF. Use it to manage dependencies between jobs, monitor job completion status, restart failed jobs without rerunning jobs that finished successfully, and more! -
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ReScaGrid stands for REsource SCAvenging Grid. This project executes Javascript on compute engines and returns results back to a central task broker. It is designed to scavenge unused compute resources (e.g. user desktops) for bacth computation.
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This is an AJAX-style website based in PHP that permits an individual or group to configure, launch, and control virtual machine instances under the Amazon Elastic Compute Cloud.
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PPIV is a parallel software application used in Particle Image Velocimetry (PIV) analysis. The software will compute the vector field for one image pair or multiple image pairs. PPIV can run on a single desktop machine or in a cluster environment.
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"Distributed breve" (distbreve) is an open-source software package to make the process of implementing asynchronous, parallelizable steve code running under the breve simulation environment easily distributable amongst as many compute nodes as possible.
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A set of documentation and scripts to install, configure, and manage the open-source darwin OS for use in a compute cluster environment.
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hashdeep
Compute, compare, or audit hashes.
Computes, matches, and audits hashes recursively. Supports the MD5, SHA-1, SHA-256, Tiger, and Whirlpool algorithms.
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