Search Results for "memory usage" - Page 21
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Showing 517 open source projects for "memory usage"
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ftRTOS is a tiny realtime kernel for microcontrollers focused on minimal RAM usage. Fixed priority scheduling, preemptive or cooperative multitasking, no dynamic task and memory management, all objects are defined at compile time.
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AdaptiveCells J2EE generates test-beds for benchmarking J2EE performance. They consists of highly customizable EJB cells that can emulate CPU load, memory usage, memory leaks and exceptions. The behaviour of the cells is coordinated from a web front-end.
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Servermon is designed to collect and store system parameters such as cpu load and memory usage of multiple servers in a network. Gathered information can be displayed and compared in a Web-Frontend.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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sysprofd is a system profiling daemon that can report results through a tcp connection to a remote client. sysprofd profiles cpu, memory, and swap usage statistics, process status statistics e.t.c. Imagine using it to easily monitor lots of linux boxes
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JavaSysInfo is the java version of phpSysInfo, a library that provides information on the host being accessed. It parses /proc and displays things like Uptime, CPU, Memory, SCSI, IDE, PCI, Network adaptors and traffic, Disk usage and Video Information
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A compact java library for securely maintaining web client state on the client side (e.g. browser) rather than on the server. This solves the many problems with using a server session such as timeouts, memory usage, network latency (with using a cluster)
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The welofunc project will develop a load and fuctional test tool for web applications with special focus on J2EE applications. Besides load and functional tests server monitoring will be included (CPU load, memory usage of the J2EE application server)
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Performance Info Service is a small configurable applet that displays performance counter data such as CPU usage, page file, system, physical memory usage, ip address, computer name, process/thread count, and system uptime on Windows NT and 2000.
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Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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YASE is a screen editor designed to be portable enough to have a consistent interface across all platforms, to minimize memory usage and still maintain a high degree of configurability.
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Nemotron 3
Large language model developed and released by NVIDIA
...It is the post-trained and FP8-quantized variant of the Nemotron 3 Nano model, meaning its weights and activations are represented in 8-bit floating point (FP8) to dramatically reduce memory usage and computational cost while retaining high accuracy. The base Nano architecture uses a hybrid Mamba-Transformer Mixture-of-Experts (MoE) design, allowing the model to activate only a small fraction of its 31.6 billion parameters per token, which improves speed and efficiency without sacrificing quality on complex queries. ... -
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Nemotron 3 Super
Open language model developed by NVIDIA as part of Nemotron-3 family
...The model contains approximately 120 billion parameters, but employs a Mixture-of-Experts architecture that activates only a smaller subset of parameters during inference, improving computational efficiency while maintaining high capability. Its architecture combines Transformer attention layers with Mamba state-space components to balance long-context reasoning, memory efficiency, and high-quality language generation. The model is optimized for building AI agents that must perform complex tasks such as planning, tool usage, coding assistance, and multi-step reasoning. -
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Laguna XS.2
Open agentic coding model optimized for local deployment
Laguna XS.2 is Poolside’s first open-weight Mixture-of-Experts model designed specifically for agentic coding and long-horizon software engineering tasks. The model contains 33B total parameters with only 3B activated per token, allowing it to deliver strong coding performance while remaining efficient enough to run locally on modern consumer hardware. It uses a hybrid attention architecture that combines Sliding Window Attention and global attention layers, reducing memory requirements and... -
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DiffusionGemma
NVFP4 DiffusionGemma model for fast multimodal text generation
DiffusionGemma 26B A4B IT NVFP4 is NVIDIA’s Model Optimizer quantized release of Google DeepMind’s DiffusionGemma 26B A4B IT model. It is an open-weights multimodal generative model that processes text, images, and video inputs to produce text output through discrete diffusion. Built on the Gemma 4 26B A4B Mixture-of-Experts architecture, it has 25.2B total parameters and 3.8B active parameters, balancing capability with efficient inference. Its diffusion-based generation produces tokens in... -
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MiMo-V2.5-Pro
Flagship MoE model for long-context agents and complex coding
...The model supports a 1 million token context window, enabling it to maintain coherence across long workflows involving thousands of tool calls and multi-step reasoning chains. Architecturally, it uses a hybrid attention system combining Sliding Window Attention and Global Attention to significantly reduce memory usage while preserving long-context performance. It also integrates multi-token prediction modules that accelerate inference and improve reinforcement learning efficiency. Trained on around 27 trillion tokens with FP8 mixed precision and refined through supervised fine-tuning, large-scale agentic reinforcement learning, and distillation. -
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EasyStream
Java library that ease the task to use streams.
...EasyStream is a natural extension of Apache commons-io ( http://commons.apache.org/io/ ), providing advanced solutions to some common but not trivial problem. This library key points are performances, low memory footprint, reduced set of dependencies and simplicity of usage. -
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Mistral Large 3 675B Instruct 2512 NVFP4
Quantized 675B multimodal instruct model optimized for NVFP4
Mistral Large 3 675B Instruct 2512 NVFP4 is a frontier-scale multimodal Mixture-of-Experts model featuring 675B total parameters and 41B active parameters, trained from scratch on 3,000 H200 GPUs. This NVFP4 checkpoint is a post-training-activation quantized version of the original instruct model, created through a collaboration between Mistral AI, vLLM, and Red Hat using llm-compressor. It retains the same instruction-tuned behavior as the FP8 model, making it ideal for production...
