PRESENTATION
Organização da memória em GPUs (NVIDIA/AMD)
Start
O que é uma GPU (Unidade de Processamento Gráfico)?
A GPU (Graphics Processing Unit) é um microprocessador especializado no processamento de gráficos, imagens e vídeos com alta eficiência. Sua arquitetura é projetada para realizar cálculos complexos de forma paralela, o que a torna ideal para lidar com grandes volumes de dados visuais. Função Principal O objetivo central da GPU é otimizar o desempenho do sistema, aliviando a carga de trabalho da CPU (Central Processing Unit). Ao assumir tarefas computacionalmente intensivas e repetitivas, a GPU permite que o processador principal se concentre na execução do sistema operacional e de outras aplicações de uso geral.
Diferenças entre CPU e GPU e suas Áreas de Atuação
Diferentemente da CPU, que realiza processamento sequencial de tarefas complexas, a GPU é projetada para processamento paralelo, com milhares de núcleos especializados operando simultaneamente. Isso permite que a GPU seja altamente eficiente em tarefas que demandam muita computação simultânea.
Principais Áreas de Atuação
- Entretenimento: Jogos digitais de alta fidelidade e renderização 3D em tempo real.
- Produção Visual: Edição e pós-produção de vídeos em resoluções ultra-altas.
- Inovação: Treinamento de modelos de Inteligência Artificial (IA) e Machine Learning.
- Pesquisa: Simulações científicas complexas e análise de grandes volumes de dados.
Empresas como NVIDIA e AMD lideram o setor com tecnologias de ponta, impulsionando avanços em diversas áreas que dependem de alta capacidade de processamento paralelo.
Hierarquia de Memória
Hierarquia de Memória em GPUs
A hierarquia de memória em GPUs é projetada para otimizar o desempenho, maximizando a largura de banda e minimizando a latência. Essa organização permite o processamento eficiente de grandes volumes de dados em paralelo. A estrutura varia dependendo da arquitetura e do fabricante, mas geralmente segue uma ordem do mais rápido ao mais lento:
- Registradores: memória mais rápida, usada para operações instantâneas
- Cache L1 / Memória Compartilhada: acessos rápidos para threads próximas
- Cache L2: maior, mas um pouco mais lento, compartilhada por múltiplos núcleos
- Memória Global (VRAM): memória de vídeo de alta largura de banda
- Memória do Sistema (RAM): mais lenta, usada para armazenamento geral
Essa hierarquia é essencial para alcançar alto desempenho em operações paralelas em GPUs.
Registradores (Registers)
Principais características:
Como funcionam na prática:
- Alocação Exclusiva: Cada thread possui seu próprio conjunto de registradores, permitindo execução rápida e isolada de tarefas.
- Acesso de Ultra Velocidade: Registradores armazenam dados de uso frequente, eliminando a necessidade de acessar a VRAM, o que acelera o processamento.
- Eficiência de Ciclo: Essas características possibilitam que a GPU realize cálculos complexos de forma eficiente, mantendo-se no núcleo de processamento e maximizando o desempenho. Essa arquitetura otimiza o processamento paralelo e melhora o throughput geral da GPU.
- Os registradores na GPU são recursos limitados. Quando a demanda excede a capacidade, ocorre o transbordamento, aumentando a latência e degradando o desempenho, o que reduz a taxa de quadros (FPS) e aumenta o tempo de renderização. Gerenciar eficientemente esses recursos é essencial para otimizar o desempenho gráfico.
- Os registradores representam o nível mais rápido de memória, localizados internamente em cada núcleo de processamento, permitindo acesso imediato aos dados.
- Utilizados durante cálculos, eles eliminam a latência, ou seja, o tempo de espera para acessar informações.
- Uma gestão eficiente dos registradores garante máximo desempenho, reduzindo a necessidade de buscar dados em memórias externas mais lentas.
- Caso essa gestão seja inadequada, pode ocorrer um gargalo de performance, forçando a GPU a diminuir tarefas paralelas, o que impacta na fluidez de jogos e na velocidade de renderizações.
PROCESs 01
PROCESs 02
PROCESs 03
Memória Compartilhada / Cache L1
Principais características:
Como funcionam na prática:
- Memória de baixa latência localizada dentro do chip da GPU permite acesso extremamente rápido aos dados, reduzindo atrasos na execução de tarefas
- A proximidade física, junto aos núcleos, elimina o tempo de deslocamento de dados, otimizando o desempenho
- Em arquiteturas modernas, como NVIDIA e AMD, há uma gestão híbrida onde o espaço físico é único e configurado dinamicamente entre a memória L1 e a memória compartilhada, garantindo flexibilidade e eficiência
- Na NVIDIA, essa memória reside nos SMs (Streaming Multiprocessors), enquanto na AMD ela está nas CUs (Compute Units), facilitando o acesso rápido e eficiente às informações necessárias para processamento
- Sincronização permite que threads do mesmo bloco compartilhem resultados parciais em um espaço comum, como um 'quadro branco'. Isso garante que todas as threads estejam alinhadas durante o processamento.
- Filtro de Dados atua como um seletor, retendo informações mais acessadas para evitar buscas na VRAM, que é mais lenta. Assim, melhora-se o desempenho ao otimizar acessos.
- Reutilização é eficiente em tarefas onde um dado, lido uma única vez da VRAM, é utilizado por centenas de núcleos simultaneamente. Essa abordagem maximiza o uso dos recursos da GPU, aumentando a eficiência do processamento.
Desempenho:
- Economia de Banda: Menor tráfego com a memória externa
- Ganho de Escala: Aumenta a eficiência em tarefas paralelas massivas (IA, Jogos, Renderização)
- Fluidez: Redução drástica da latência de acesso, garantindo tempos de execução menores
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- Make sure your audience remembers the message.
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- Generate experiences with your content.
- It’s got the Wow effect. Very Wow.
- Make sure your audience remembers the message.
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Let the communication flow!
With Genially templates, you can include visual resources to wow your audience. You can also highlight a particular sentence or piece of information so that it sticks in your audience’s minds, or even embed external content to surprise them: Whatever you like! Do you need more reasons to create dynamic content? No problem! 90% of the information we assimilate is received through sight and, what’s more, we retain 42% more information when the content moves.
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Organização da memória em GPUs (NVIDIA/AMD)
Ramon Martins da Silva
Created on April 20, 2026
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Transcript
PRESENTATION
Organização da memória em GPUs (NVIDIA/AMD)
Start
O que é uma GPU (Unidade de Processamento Gráfico)?
A GPU (Graphics Processing Unit) é um microprocessador especializado no processamento de gráficos, imagens e vídeos com alta eficiência. Sua arquitetura é projetada para realizar cálculos complexos de forma paralela, o que a torna ideal para lidar com grandes volumes de dados visuais. Função Principal O objetivo central da GPU é otimizar o desempenho do sistema, aliviando a carga de trabalho da CPU (Central Processing Unit). Ao assumir tarefas computacionalmente intensivas e repetitivas, a GPU permite que o processador principal se concentre na execução do sistema operacional e de outras aplicações de uso geral.
Diferenças entre CPU e GPU e suas Áreas de Atuação
Diferentemente da CPU, que realiza processamento sequencial de tarefas complexas, a GPU é projetada para processamento paralelo, com milhares de núcleos especializados operando simultaneamente. Isso permite que a GPU seja altamente eficiente em tarefas que demandam muita computação simultânea. Principais Áreas de Atuação
- Entretenimento: Jogos digitais de alta fidelidade e renderização 3D em tempo real.
- Produção Visual: Edição e pós-produção de vídeos em resoluções ultra-altas.
- Inovação: Treinamento de modelos de Inteligência Artificial (IA) e Machine Learning.
- Pesquisa: Simulações científicas complexas e análise de grandes volumes de dados.
Empresas como NVIDIA e AMD lideram o setor com tecnologias de ponta, impulsionando avanços em diversas áreas que dependem de alta capacidade de processamento paralelo.Hierarquia de Memória
Hierarquia de Memória em GPUs A hierarquia de memória em GPUs é projetada para otimizar o desempenho, maximizando a largura de banda e minimizando a latência. Essa organização permite o processamento eficiente de grandes volumes de dados em paralelo. A estrutura varia dependendo da arquitetura e do fabricante, mas geralmente segue uma ordem do mais rápido ao mais lento:
Essa hierarquia é essencial para alcançar alto desempenho em operações paralelas em GPUs.Registradores (Registers)
Principais características:
Como funcionam na prática:
PROCESs 01
PROCESs 02
PROCESs 03
Memória Compartilhada / Cache L1
Principais características:
Como funcionam na prática:
Desempenho:
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Author's name
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LOREM IPSUM DOLOR
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ViDEO
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PROCESS
PROCESs 01
PROCESs 02
PROCESs 03
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PROCESS
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VS
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timeline
2000
2010
2020
2030
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timeline
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Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet
2020
Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet
2030
Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet
2040
MAP
25%
65%
Lorem ipsum dolor sit amet, consectetuer adipiscing elit
WRITE YOUR TITLE HERE
75%
Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat.
+ info
LOREM IPSUM DOLOR
Lorem ipsum dolor sit amet consectetuer
35%
+ info
Lorem ipsum dolor sit amet consectetuer
20%
+ info
Lorem ipsum dolor sit amet consectetuer
55%
+ info
LOREM IPSUM DOLOR
Lorem ipsum dolor sit amet, consectetuer adipiscing elit
team
NAME
NAME
name
NAME
Lorem ipsum dolor sit amet, consectetuer
Lorem ipsum dolor sit amet, consectetuer
Lorem ipsum dolor sit amet, consectetuer
Lorem ipsum dolor sit amet, consectetuer
team
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With Genially templates, you can include visual resources to wow your audience. You can also highlight a particular sentence or piece of information so that it sticks in your audience’s minds, or even embed external content to surprise them: Whatever you like! Do you need more reasons to create dynamic content? No problem! 90% of the information we assimilate is received through sight and, what’s more, we retain 42% more information when the content moves.
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Let the communication flow!
With Genially templates, you can include visual resources to wow your audience. You can also highlight a particular sentence or piece of information so that it sticks in your audience’s minds, or even embed external content to surprise them: Whatever you like! Do you need more reasons to create dynamic content? No problem! 90% of the information we assimilate is received through sight and, what’s more, we retain 42% more information when the content moves.
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Let the communication flow!
With Genially templates, you can include visual resources to wow your audience. You can also highlight a particular sentence or piece of information so that it sticks in your audience’s minds, or even embed external content to surprise them: Whatever you like! Do you need more reasons to create dynamic content? No problem! 90% of the information we assimilate is received through sight and, what’s more, we retain 42% more information when the content moves.
Got an idea?
Let the communication flow!
With Genially templates, you can include visual resources to wow your audience. You can also highlight a particular sentence or piece of information so that it sticks in your audience’s minds, or even embed external content to surprise them: Whatever you like! Do you need more reasons to create dynamic content? No problem! 90% of the information we assimilate is received through sight and, what’s more, we retain 42% more information when the content moves.