Revolutionize AI Acceleration with Boca Ria: Next-Gen Memory Inference

Table of Contents:

1. Introduction
2. The Evolution of AI and Neural Networks
3. The Challenges in AI Workloads
4. The Architecture of Boca Ria: At Memory Compute
   • 4.1 The Role of Data Movement in Neural Network Compute
   • 4.2 The Efficient Data Movement Solution
   • 4.3 Coarse-Grained Architecture for Compute Performance
   • 4.4 Different Data Types for Accuracy and Efficiency
5. The Benefits of Boca Ria's Spatial Architecture
6. Scaling and Flexibility of Boca Ria
   • 6.1 Scalability for Different Form Factors and Power Envelopes
   • 6.2 Chiplet Ready for Integration with SoCs
7. Performance and Energy Efficiency of Boca Ria
   • 7.1 Impressive Performance Metrics
   • 7.2 Energy Efficiency for Higher Throughput
8. Boca Ria's PCI Express Card and Interconnectivity
9. The Importance of Software Support
   • 9.1 The Imagine Software Development Kit
   • 9.2 Replication of Layers for Enhanced Performance
10. Future Potential: Stacked 3D SRAM Memory
11. Conclusion

📣 Highlights:

• Boca Ria, a next-generation memory inference acceleration device, is introduced at Hot Chips.
• It offers two petaflops of inference acceleration with 30 tops per watt energy efficiency.
• Boca Ria addresses the challenges of increasing computational requirements, architecture flexibility, and efficiency in AI workloads.
• The spatial architecture of Boca Ria enables scalability and supports various form factors and power envelopes.
• Boca Ria outperforms existing solutions in terms of throughput and energy efficiency, making it ideal for natural language processing networks.

The Next Generation of Memory Inference Acceleration with Boca Ria

Introduction

Artificial intelligence (AI) has witnessed tremendous growth in recent years, thanks to advancements in neural networks and computational capabilities. To keep up with the increasing demands of AI workloads, the development of specialized hardware accelerators has become crucial. One such innovation is Boca Ria, a memory inference acceleration device introduced at Hot Chips.

The Evolution of AI and Neural Networks

Over the last decade, the field of AI has witnessed a significant transformation, largely driven by the introduction of neural networks. The breakthrough AlexNet paper, released just ten years ago, marked the beginning of the current AI summer. Since then, the development of various neural network architectures has exploded, enabling unprecedented advancements in AI technologies.

The Challenges in AI Workloads

As neural networks become more complex and demanding, developers face several challenges. Firstly, there is a need for increased computational power to meet the requirements of AI workloads. Secondly, architects must account for the power efficiency necessary for these demanding tasks. Finally, the rapidly evolving landscape of neural networks requires a flexible architecture capable of adapting to changing requirements. Additionally, ensuring accuracy while maintaining energy efficiency is of utmost importance.

The Architecture of Boca Ria: At Memory Compute

To tackle the challenges of AI workloads, Boca Ria was developed with an architecture that combines a fine balance of coarse-grained compute performance and optimized data movement. It utilizes an innovative at memory compute approach, which focuses on the efficient movement of data within the memory itself. This approach aims to minimize energy consumption while maximizing computational efficiency.

The Efficient Data Movement Solution

Traditionally, a significant portion of energy in neural network compute is spent on data movement. Boca Ria flips this paradigm by placing the compute elements directly attached to memory cells. By minimizing data travel distances, this innovative architecture achieves remarkable energy efficiency. While other memory compute approaches may suffer from analog effects and additional circuitry requirements, Boca Ria leverages standard digital logic processes, ensuring both efficiency and performance.

Coarse-Grained Architecture for Compute Performance

Boca Ria's architecture is carefully designed to support the required level of compute granularity for accelerating neural networks effectively. The memory bank smart memory, comprising dual risk-5 processors, enriches the computational capabilities. Each memory bank consists of various controllers and subcontrollers operating at unprecedented speed, enabling efficient communication within the network.

Different Data Types for Accuracy and Efficiency

Ensuring accuracy in AI workloads is critical, especially in applications like recommendation engines and autonomous vehicles. Boca Ria addresses this challenge by supporting multiple data types. While fp32 offers ultimate accuracy, the computational requirements are high. In contrast, Boca Ria introduces the bf16 and fp8 data types that quadruple energy efficiency while preserving the necessary accuracy. This flexibility allows users to optimize their applications based on accuracy and throughput requirements.

The Benefits of Boca Ria's Spatial Architecture

Boca Ria's spatial architecture provides numerous benefits, including scalability and performance optimizations. With the ability to Scale from sub-1 watt devices to infrastructure-class devices, it caters to various power envelopes and form factors. Additionally, its chiplet-ready design allows for direct die-to-die integration, providing ultimate flexibility for system-on-chip (SoC) implementations.

Scaling and Flexibility of Boca Ria

Scalability is a key consideration in the design of Boca Ria. By incorporating direct chip-to-chip interconnect using PCI Express, multiple chips can be seamlessly integrated to support the largest natural language processing networks. Furthermore, Boca Ria's spatial architecture enables the creation of smaller devices by reducing the number of memory banks while maintaining performance and efficiency.

Performance and Energy Efficiency of Boca Ria

Boca Ria sets new milestones in performance and energy efficiency, offering two petaflops of inference acceleration with an impressive 30 teraflops per watt. Compared to existing solutions, Boca Ria provides significant throughput advantages for vision networks and delivers eight times greater throughput and 15 times greater energy efficiency for natural language processing networks like BERT-base.

Boca Ria's PCI Express Card and Interconnectivity

To facilitate easy integration into existing systems, Boca Ria is designed to fit on a PCI Express card. Each card can accommodate up to six Boca Ria devices, providing substantial SRAM capability for scaling to the largest language models. With chip-to-chip interconnectivity supported by PCI Express, powerful server implementations can be constructed, offering unparalleled performance for demanding applications.

The Importance of Software Support

Software plays a crucial role in maximizing the potential of Boca Ria's hardware. The Imagine Software Development Kit (SDK) simplifies the process of bringing neural networks onto the Boca Ria platform. It automatically optimizes and lowers the graph, provides comprehensive analysis tools, and supports fine-tuning for specific applications. The SDK's easy-to-use runtime integration supports seamless adoption of Boca Ria across various machine learning frameworks.

Future Potential: Stacked 3D SRAM Memory

While Boca Ria currently utilizes on-chip SRAM, future advancements in memory technologies will continue to be monitored. Stacked 3D SRAM memory, if proven to be manufacturable and cost-effective at scale, could offer further performance and energy efficiency improvements. Boca Ria is committed to adopting the most suitable memory technology to ensure optimal results.

Conclusion

Boca Ria represents the next generation of memory inference acceleration, addressing the challenges of increasing computational requirements, architectural flexibility, and energy efficiency in AI workloads. With its innovative architecture, Boca Ria offers impressive performance metrics, scalability, and the flexibility to support various data types. By achieving unparalleled energy efficiency and throughput, Boca Ria is poised to revolutionize AI acceleration and open new possibilities for the future of artificial intelligence.

📚 Resources:

• Hot Chips Conference
• Untether AI

💡 Frequently Asked Questions:

Q: How does Boca Ria achieve high energy efficiency? A: Boca Ria's at memory compute architecture places compute elements directly attached to memory cells, minimizing data movement and reducing energy consumption.

Q: What data types does Boca Ria support? A: Boca Ria supports multiple data types, including fp32, bf16, and fp8, allowing users to optimize for accuracy and efficiency based on their specific application requirements.

Q: Can Boca Ria scale to larger models and networks? A: Yes, Boca Ria offers scalability by integrating multiple chips using chip-to-chip interconnectivity, allowing users to scale to the largest natural language processing networks.

Q: What software support does Boca Ria provide? A: Boca Ria offers the Imagine Software Development Kit (SDK), which simplifies the development process by automatically lowering neural networks, providing analysis tools, and supporting runtime integration with popular machine learning frameworks.

Q: Are there plans to submit Boca Ria for mlperf benchmarks? A: While it's on the roadmap, submission to mlperf benchmarks depends on resource availability and is not imminent.

Q: Does Boca Ria support stacked 3D SRAM memory? A: Boca Ria currently utilizes on-chip SRAM, but future advancements in memory technologies, such as stacked 3D SRAM, are continuously monitored for potential implementation.