graphics processing unit
PulseAugur coverage of graphics processing unit — every cluster mentioning graphics processing unit across labs, papers, and developer communities, ranked by signal.
- used by Vulkan 90%
- used by Triton 90%
- used by central processing unit 70%
- competes with Tensor Processing Unit 70%
- competes with application-specific integrated circuit 70%
- competes with Apple Neural Engine 70%
- instance of high-performance computing 70%
- used by AI inference 70%
- used by H.1000 Gnome 70%
- used by Innu-aimun 70%
- competes with Cerebras Systems 70%
- used by SemiAnalysis 70%
29 day(s) with sentiment data
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Commentator calls AI boom a 'giant con' reliant on hyperscalers
Tech commentator Ed Zitron argues that the current AI boom, particularly for companies like OpenAI and Anthropic, is an unsustainable "con" propped up by hyperscalers. He believes this reliance on massive infrastructure…
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GPU Memory Bandwidth Crucial for Local LLM Speed, Outpacing VRAM
For running large language models locally, GPU memory bandwidth is a more critical factor than VRAM capacity. Higher bandwidth allows the GPU to process data more quickly, preventing it from being bottlenecked while wai…
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New GPU solver cuRegOT accelerates optimal transport for machine learning
Researchers have developed cuRegOT, a new GPU-accelerated solver designed to overcome the computational challenges of optimal transport (OT) in large-scale machine learning applications. The solver addresses the limitat…
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Mac mini outperforms expensive workstations running large AI models
A $1,999 Mac mini equipped with Apple Silicon can run a 70-billion parameter AI model, outperforming a $4,000 Windows workstation. This is attributed to Apple's unified memory architecture, which eliminates VRAM and PCI…
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Kunluncore files for dual IPO, touts China's first 32K GPU AI cluster
Kunluncore, an AI chip spinoff from Baidu, has officially filed for an IPO on Shanghai's STAR Market, alongside a concurrent filing for a Hong Kong listing on January 1st. The company announced its P800 GPU cluster, fea…
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HCInfer system enables LLMs on resource-constrained devices with error compensation
Researchers have developed HCInfer, a novel inference system designed to enable large language models (LLMs) to run efficiently on devices with limited memory. This system offloads parts of the model's compensation mech…
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Rongxin Zhiyuan raises hundreds of millions for GPU-centric AI architecture
Rongxin Zhiyuan, an AI infrastructure company founded by Tsinghua University alumni, has secured hundreds of millions of yuan in an angel funding round. The company is developing its novel AGC architecture, which positi…
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Galaxy Securities: Token consumption to surge, benefiting AIDC, telcos, fiber optics, and optical modules
Galaxy Securities predicts a significant increase in Token consumption, driven by the growing demand for AI inference and rapid iteration of large language models. This surge is expected to accelerate growth across four…
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AWS offers EC2 Capacity Blocks for short-term GPU needs
Amazon Web Services (AWS) is introducing EC2 Capacity Blocks for Machine Learning (ML) and SageMaker training plans to address the scarcity of GPU capacity. These new options allow customers to secure short-term GPU res…
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Modal boosts multimodal inference performance over 10% with Python dict
Modal has identified a performance bottleneck in multimodal inference engines like SGLang, which can hinder GPU utilization. By profiling the scheduler, they discovered that expensive bookkeeping for shared GPU memory c…
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New benchmark reveals LLM-generated GPU kernels struggle with correctness and efficiency
A new benchmark called KernelBench-X has been developed to evaluate the capabilities of large language models in generating GPU kernels. The benchmark, which covers 176 tasks across 15 categories, reveals that task stru…
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AMD EPYC CPUs show competitive performance for LLM and TTS inference workloads
A recent analysis by Leaseweb benchmarks the performance of AMD EPYC 9334 CPUs for Large Language Model (LLM) and Text-to-Speech (TTS) inference workloads. The study reveals that while GPUs offer higher throughput, CPUs…
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AI assists in developing Pascal version of LAPACK, aiming for GPU acceleration
A user on Mastodon is collaborating with GitHub Copilot to develop a Pascal version of the LAPACK numerical library, which is approximately 30% complete. They anticipate reaching 80% completion within two days and plan …
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New tool cuts GPU memory use in AI training by optimizing optimizer states
Researchers have developed a Budget-Aware Optimizer Configurator (BAOC) to address the significant GPU memory consumption during large-scale model training. BAOC intelligently assigns different optimizer configurations …
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AI image generation: CPU vs GPU performance and scaling insights
This article explores the performance differences between CPUs and GPUs when generating AI-created images and videos. The author shares their experience using these components for digital art creation, highlighting that…
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Memory giants push new MRDIMM standard for AI, HPC servers
Major memory manufacturers Samsung Electronics, SK Hynix, and Micron are nearing completion of the next-generation server DRAM module standard, MRDIMM. This new standard is optimized for AI and high-performance computin…
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New Polar Express method accelerates matrix decomposition for deep learning
Researchers have developed a new GPU-friendly algorithm called Polar Express for computing matrix decompositions, which is crucial for the Muon optimizer used in training deep neural networks. This method optimizes for …
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VUDA system enables spatial sharing of compute and graphics on GPUs
Researchers have developed VUDA, a system designed to enhance GPU utilization by enabling simultaneous execution of CUDA compute and Vulkan graphics workloads. This is achieved by breaking down the isolation between the…
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Lumentum CEO: AI component demand outstrips supply, orders booked until 2028
Lumentum, a major US optical module manufacturer, reported a record-breaking third fiscal quarter with revenue soaring 90% year-over-year to $808 million. The company also saw significant improvements in profitability, …
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AI boom creates volatile market for video game hardware
The burgeoning AI industry is creating unprecedented demand for high-end graphics cards, significantly impacting the video game hardware market. This surge in demand is leading to shortages and price increases for GPUs,…