TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate…
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT. (⭐ 12759)
11th gen Alder Lake processors and Nvidia RTX 30 series GPUs. Thinnest 15-inch Alienware laptop so far. Alienware M15 R7 – 2022 thin and light gaming
Meta is with AMD. We’re partnering with AMD to integrate their GPUs into our infrastructure—that means more compute power to bring our AI experiences to even more people.
CodeXL is a comprehensive tool suite that enables developers to harness the benefits of CPUs, GPUs and APUs. (⭐ 1000)
This study was aimed at simultaneously achieving sufficient accuracy and high performance for general matrix multiplications. Recent architectures, such as NVIDIA GPUs, feature high-performance units designed for low-precision matrix multiplications...
CUDA on non-NVIDIA GPUs (⭐ 13986)
Graphics Processing Units (GPUs) are over-stressed to accelerate High-Performance Computing applications and are used to accelerate Deep Neural Networks in several domains where they have a life expectancy of many years. These conditions expose the G...
Unlock vGPU functionality for consumer grade GPUs. (⭐ 5216)
Existing GPU libraries often struggle to fully exploit the parallel resources and on-chip memory (SRAM) of GPUs when chaining multiple GPU functions as individual kernels. While Kernel Fusion (KF) techniques like Horizontal Fusion (HF) and Vertical F...
John the Ripper jumbo - advanced offline password cracker, which supports hundreds of hash and cipher types, and runs on many operating systems, CPUs, GPUs, and even some FPGAs (⭐ 12811)
Designing programming environments for physical simulation is challenging because simulations rely on diverse algorithms and geometric domains. These challenges are compounded when we try to run efficiently on heterogeneous parallel architectures. We...
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes. (⭐ 30905)
We propose an incomplete algorithm for Maximum Satisfiability (MaxSAT) specifically designed to run on neural network accelerators such as GPUs and TPUs. Given a MaxSAT problem instance in conjunctive normal form, our procedure constructs a Restricte...
Genetic Programming (GP) is a computationally intensive technique which is naturally parallel in nature. Consequently, many attempts have been made to improve its run-time from exploiting highly parallel hardware such as GPUs. However, a second metho...
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13th generation Intel Core 'Raptor Lake-S' processors and Nvidia Quadro T400 or T1000 Turing-based workstation GPUs. The updated ThinkStations have a baseboard
processing units (GPUs) and video cards from Nvidia, based on official specifications. In addition some Nvidia motherboards come with integrated onboard
The cost of combustion simulations is often dominated by the evaluation of net production rates of chemical species and mixture thermodynamics (thermochemistry). Execution on computing accelerators (XPUs) like graphic processing units (GPUs) can grea...
Training machine learning (ML) models on large datasets requires considerable computing power. To speed up training, it is typical to distribute training across several machines, often with specialized hardware like GPUs or TPUs. Managing a distribut...
I was using vast AI for fine tuning using unsloth, and I have tried changing 10 different GPUs but every other gpu has some problem and it never works. First I was using RTX 5090 and the terminal keep...
"Attention Is All You Need" is the seminal paper that set off the generative AI revolution we are all experiencing. Raise your GPUs today for these incredibly smart and important people. ...
In this paper we want to address the problem of automation for recognition of photographed cooking dishes and generating the corresponding food recipes. Current image-to-recipe models are computation expensive and require powerful GPUs for model trai...
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This paper proposes a type of pseudorandom number generator, Mersenne Twister for Graphic Processor (MTGP), for efficient generation on graphic processessing units (GPUs). MTGP supports large state sizes such as 11213 bits, and uses the high parallel...
I introduce a new code for fast calculation of the Lomb-Scargle periodogram, that leverages the computing power of graphics processing units (GPUs). After establishing a background to the newly emergent field of GPU computing, I discuss the code desi...
So i want to full parameter fintune mistral 7b model on my custom dataset i have access to 4 A10G gpus which they have 96 GB in total and maybe 8 A100G 40GB which makes 320 GB in total usin...
Yet another alternative.
In an interview with CNBC, Nvidia CEO Jensen Huang said his company's project with OpenAI is equivalent to between 4 million and 5 million GPUs.
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Find out what a GPU is, how they work, and their uses for parallel processing with a definition and description of graphics processing …
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GPU tier list 2026: RTX 5090, 5070, RX 9070 XT and 150+ cards ranked by real gaming benchmarks. Find the best GPU for your …
active since 1984. In 2001, the GPUS was officially founded as the ASGP split from the G/GPUSA. After its founding, the GPUS soon became the primary national