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최적의 성능을 위한 웨이퍼 스케일 프로세서를 갖춘 AI 가속의 선두주자.
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3월 20 2025
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Cerebras 제품 정보

Cerebras이란 무엇인가요?

Cerebras는 인공지능 가속의 선두주자로서, 심층 학습, 자연어 처리 및 다양한 AI 작업을 위해 뛰어난 성능을 제공하는 웨이퍼 스케일 프로세서에 전문화되어 있습니다. 이들의 기술은 대규모 AI 시스템 및 어플리케이션, 추론 서비스, 고성능 컴퓨팅 및 산업별 솔루션을 지원합니다. 이 회사는 개발자, 연구자 및 첨단 AI 기능을 찾는 기업을 위한 더 빠르고 효율적인 AI 모델 교육 및 배포를 가능하게 하는 데 중점을 둡니다.

Cerebras을 어떻게 사용하나요?

Cerebras를 사용하려면 다양한 AI 모델 서비스를 탐색하고, 필요에 맞는 솔루션을 선택한 후, 구현 가이드를 위한 개발자 리소스에 액세스하십시오.

Cerebras의 핵심 기능

심층 학습을 위한 웨이퍼 스케일 프로세서

고속 추론 기능

클라우드 기반 AI 모델 서비스

Cerebras의 사용 사례

#1

AI 모델 교육 및 배포 가속화

#2

복잡한 모의를 위한 고성능 컴퓨팅 활용

Cerebras의 FAQ

Cerebras AI의 주요 목적은 무엇인가요?

Cerebras 추론 서비스에 접근할 수 있나요?

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cerebras
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$ 2.10
cerebras systems
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cerebras ai
--
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cerebras coder
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cerebras inference
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검색 기록
41:26

How massive Cerebras chips rival Nvidia GPUs for AI

I interviewed Joel Hestness, a key engineer at Cerebras. Cerebras produces AI accelerators like Groq and Nvidia, but Cerebras focuses on producing the largest chips possible. Their chips use an entire silicon wafer, and contain a million cores (the same way Nvidia gpus contain a few tens of thousands of Cuda cores). We discuss in detail how the memory architecture works for such a unique system, cooling, compiler architecture, logical mapping of cores, etc. One of the most interesting aspects is that the hardware can handle arbitrary failures of specific cores, which is necessary because almost any wafer would have some faults in it that would cause cores to stop working. Cerebras is price competitive with Nvidia GPUs but can perform inference many times faster on just a single node. For training, many nodes can be networked together. They demonstrate support for multi-trillion parameter models, and have out of the box support for open source models like Llama 3.3. Very interesting hardware, and I hope the company sees success in the market. #ai #hardware #accelerators Cerebras https://cerebras.ai/ Announcing Cerebras Inference Research Grant https://cerebras.ai/blog/grantfrp Joel Hestness https://www.linkedin.com/in/joelhestness 0:00 Intro 0:15 Contents 0:27 Part 1: Introduction 0:43 Experience at Baidu research lab 1:57 Exposure to hardware companies like Cerebras 2:33 Focus on pretraining at Cerebras 3:27 Overview of Cerebras, using a giant wafer to accelerate AI 4:24 Very large scale trillion parameter models 5:40 How many GPUs is this equivalent to? 6:19 How much memory is in one Cerebras chip? 7:32 Activations (in SRAM) vs weights (off chip) 8:18 New inference solution, 4x faster than anything else 9:13 Enough memory for a 24 trillion parameter model?? 10:26 Cerebras more flexible than other hardware approaches 11:42 High performance computing stack 13:03 Part 2: The hardware 13:15 How large are these chips anyway? 14:02 One million cores 14:38 Logical array of cores 15:23 Mapping out cores that aren't working 16:10 IBM Cell processor comparison 16:57 Dealing with defects in the wafer for 100% yield 18:11 It's almost like having a million separate chips 18:36 Stress testing the chips to find defects 19:20 Types of issues: stalls, bit flips, etc 19:51 Ryzen segfault bug comparison 20:34 So many ways to fail 21:35 Are these chips future proof against failures? 23:57 How do you keep these chips cool? 25:01 Matching the power density of Nvidia GPUs 25:39 Blackwell GPU power consumption halves number of nodes 26:47 Moving complexity out of hardware into software 27:54 Part 3: Accessing the hardware 28:07 Four different ways for customers to access 29:49 Inference API, support for Llama 3.3 30:40 Geographic distribution of Cerebras clusters 31:46 Pytorch compatibility and compiler 32:36 No custom code in pytorch needed 33:41 Details of compiler implementation 34:39 Testing 1400 hugging face models 35:47 What is the network between nodes? 36:08 Three different kinds of nodes inside Cerebras systems 36:54 How a model fits into the architecture 37:39 Whole distributed system, codesign of hardware and ML 38:38 Other supercomputing workloads 39:33 Conclusion 39:52 Cerebras has grants available 40:12 Cerebras good at inference time compute like o1 40:57 Outro

Dr Waku
12월 25 2024
31.1K
151
16:03

21 FREE AI Coding Tools THAT I USE!

Join this channel to get access to perks: https://www.youtube.com/@AICodeKing/join In this video, I'll be telling you about 21 FREE AI Coding Tools that you need to have. These tools include AI Coding Tools, Copilot Alternative, ChatGPT Alternatives, Cursor Alternatives and much more! All these tools are fully free. ---- Resources: Ollama : https://github.com/ollama/ollama OpenWebUI : https://github.com/open-webui/open-webui Mistral Free API : https://console.mistral.ai/ SambaNova : https://cloud.sambanova.ai/ Cerebras : https://cerebras.ai/ Groq : https://groq.com/ Zed AI Editor : https://zed.dev/ Aider : https://github.com/Aider-AI/aider Cline : https://github.com/cline/cline Supermaven : https://supermaven.com/ Continue : https://github.com/continuedev/continue Project IDX : https://idx.dev/ Lightning AI : https://lightning.ai/ Bolt : https://bolt.new/ DeepSeek : https://deepseek.com/ Reor : https://github.com/reorproject/reor Open Interpreter : https://github.com/OpenInterpreter/open-interpreter Jan : https://github.com/janhq/jan Perplexica : https://github.com/ItzCrazyKns/Perplexica InvokeAI : https://github.com/invoke-ai/InvokeAI Google AI Studio : https://aistudio.google.com/ ---- Key Takeaways: 🚀 Explore the Latest Free AI Tools: Discover 11 powerful free and open-source AI tools, from AI coding assistants to free VS Code interfaces, that enhance productivity and save money. Get insights into open-source alternatives to paid tools like Perplexity, Midjourney, and more! 💡 Ollama Makes AI Easy: Ollama is an open-source model inference tool that allows you to run large language models (LLMs) on your device with minimal setup. It’s perfect for quickly accessing powerful models without an OpenAI API subscription. ⚙️ Seamless Interface with OpenWebUI: Use OpenWebUI to create a ChatGPT-like interface linked to Ollama or OpenAI’s API, allowing you to experience AI chats in a friendly, visual interface right on your desktop. Docker setup is a breeze for AI developers and enthusiasts. 🌐 Mistral’s Free API: With unlimited access to the powerful Mistral Large model, Mistral’s API provides one of the most accessible LLMs on the market. Works seamlessly with OpenWebUI and other OpenAI-compatible tools! 🏎️ SambaNova API - Lightning Fast & Free: Get OpenAI compatibility with SambaNova’s free API and access Llama-3.1 for rapid, cost-effective model inference. Try SambaNova’s platform if you’re looking for speed and power in an open-source API. ⚡ Cerebras & Groq - Free and High Performance: Cerebras and Groq are leading platforms that let you use Llama models for free. Cerebras supports Llama up to 70B parameters, while Groq’s fast inference is perfect for efficient generation. 🤖 Code with Zed & Aider - Free Coding Assistants: Replace Cursor and VSCode with Zed, a fast, open-source editor powered by Claude 3.5, or Aider for a prompt-based coding experience. Both are free AI tools for developers looking for an efficient Copilot alternative. 🛠️ Cline & Supermaven - Unleash AI in VSCode: Enhance VSCode with Cline for seamless model integration or Supermaven as a fast, free copilot alternative. Boost productivity without paying for GitHub Copilot! ✨ DeepSeek - Free Chat with Claude-Level AI: DeepSeek offers Claude-like performance in coding benchmarks, for free! Chat, code, and integrate AI into projects without a subscription – DeepSeek is a must-have for coding enthusiasts. 📝 Reor - Your Free AI Notes Copilot: Reor lets you take notes with markdown support, plus AI-based summarization and chat. Ideal for students and writers, it’s compatible with Obsidian, turning note-taking into an interactive experience. 📋 Open Interpreter - Full Desktop Control via Prompts: Open Interpreter runs commands and code on your desktop through prompts, connecting with various LLM providers like Ollama. Perfect for those seeking a versatile AI assistant with OS-level control. 💻 Project IDX & Lightning AI - Code Anywhere, Free GPU Access: Project IDX by Google brings VSCode to your browser with Android emulator support, while Lightning AI offers 22 free GPU hours with VSCode access, creating the ultimate online coding environment. 🎨 Invoke for Image Generation - Free Midjourney Alternative: Invoke is an open-source web UI for image generation, making model management easy with a sleek interface. It’s perfect for creating high-quality images without the cost of Midjourney. ---- Timestamps: 00:00 - Introduction 00:51 - Ollama 02:41 - OpenWebUI 03:33 - Mistral Free API 04:18 - SambaNova 05:00 - Cerebras 05:23 - Groq 05:52 - Zed AI Editor 06:38 - Aider 07:19 - Cline 07:57 - Supermaven 08:32 - Continue 09:10 - Project IDX 09:56 - Lightning AI 10:29 - Bolt 11:10 - DeepSeek 11:59 - Reor 12:34 - Open Interpreter 13:20 - Jan 13:45 - Perplexica 14:16 - InvokeAI 14:34 - Google AI Studio 15:06 - Closing Thoughts 15:27 - Ending

AICodeKing
10월 30 2024
29.1K
58

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Cerebras 삽입 실행

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Cerebras: 최적의 성능을 위한 웨이퍼 스케일 프로세서를 갖춘 AI 가속의 선두주자.
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