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Showing 9 open source projects for "cpu benchmark linux"
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Open Source Vizier
Python-based research interface for blackbox
Open Source (OSS) Vizier is a Python-based interface for blackbox optimization and research, based on Google’s original internal Vizier, one of the first hyperparameter tuning services designed to work at scale. Allows a user to setup an OSS Vizier Server, which can host black-box optimization algorithms to serve multiple clients simultaneously in a fault-tolerant manner to tune their objective functions. Defines abstractions and utilities for implementing new optimization algorithms for... -
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Ajenti 2
Ajenti Core and stock plugins
...Plugin development is quick and pleasant with Ajenti APIs. Write your first plugin. Pleasant to look at, satisfying to click and accessible anywhere from tablets and mobile. Small memory footprint and CPU usage. Runs on low-end machines, wall plugs, routers and so on. -
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Prime number ( primenumbers )
Benchmark for 50 000 000 prime numbers as single and multicore
Simple source files and compiled JAR Java programs, for benchmark 50 000 000 cycle finding prime numbers. On Intel(R) Core(TM) i5-8600K CPU, Windows 10 20H2, i have 39 second on single core and 7,6 second on multi core. (PS: C++ multicore 6 second). Added C files for gcc compiler in Windows 10 and for Xcode C command line project in MacOS ( tested on Mac mini M2 with single core 16 to 25 sec and multicore 2,3 to 5 second by compiler -O switch). -
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DIG
A library for graph deep learning research
The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to... -
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BPF Performance Tools
Official repository for the BPF Performance Tools book
BPF Performance Tools Book is the companion repository for Brendan Gregg’s book on Linux performance analysis using eBPF and BCC tracing technologies. The project contains scripts, examples, and reference material that demonstrate how to inspect kernel behavior, application performance, CPU usage, networking activity, file systems, and system bottlenecks in real time. It serves as both an educational resource and a practical toolkit for Linux engineers, SREs, and performance analysts working with modern observability workflows. ... -
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested... -
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Learning to Learn in TensorFlow
Learning to Learn in TensorFlow
Learning to Learn, created by Google DeepMind, is an experimental framework that implements meta-learning—training neural networks to learn optimization strategies themselves rather than relying on manually designed algorithms like Adam or SGD. The repository provides code for training and evaluating learned optimizers that can generalize across different problem types, such as quadratic functions and image classification tasks (MNIST and CIFAR-10). Using TensorFlow, it defines a... -
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persistent-memory-labs
Get started with various persistent memory technologies
Persistent-memory-labs is a repository of step-by-step guides allowing a smooth approach to persistent memory technologies like NVDIMM-N. -
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The sandbox libraries (libsandbox & pysandbox) are an open-source suite of software components for C/C++ and Python developers to create automated profiling tools and watchdog programs. The API's are designed for executing and instrumenting simple (single process) tasks, featuring policy-based behavioral auditing, resource quota, and statistics collecting. The sandbox libraries were originally designed and utilized as the core security module of a full-fledged online judge system for...
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Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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