Accelerating HPC & Enterprise Workloads with Intel FPGAs

Accelerating HPC & Enterprise Workloads with Intel FPGAs

Table of Contents

• Introduction
• Role of FPGAs in the Data Center
• Deployment of FPGAs in Different Segments
  • Cloud Segment
  • High-Performance Computing (HPC)
  • Enterprise Segment
• Simplifying FPGA Programming
• The Future of FPGAs
  • Flexibility and Versatility in Deployment
  • Lower Precision Floating-Point and Machine Learning
  • New Intel FPGA Family and its Features
• Showcasing FPGA Capabilities
  • OpenCL Compression
  • NVMe over Rocky
• Conclusion

📝 Introduction

FPGAs (Field Programmable Gate Arrays) are gaining significant attention in the world of technology due to their versatility and ability to bring specialized acceleration to a wide range of applications. In this article, we will delve into the role of FPGAs in the data center, explore their deployment in various segments, discuss efforts to simplify FPGA programming, and discover the exciting future possibilities of these programmable devices.

🏢 Role of FPGAs in the Data Center

FPGAs play a crucial role in the data center by offering high-performance acceleration for specific workloads. As an architect in the Programmable Solutions Group at Intel, Mike's focus is on developing solutions for the data center, where FPGAs are utilized to enhance various operations. By leveraging the reprogrammable nature of FPGAs, organizations can achieve tailored acceleration for applications ranging from genomics to financial analysis.

💻 Deployment of FPGAs in Different Segments

☁️ Cloud Segment

The cloud segment has witnessed significant adoption of FPGAs by industry leaders such as Microsoft. FPGAs have been instrumental in accelerating Bing searches and boosting networking infrastructure. Moreover, FPGAs have found applications in machine learning, security, video transcoding, and more. Alibaba and OVH are other examples where FPGAs are exposed to accelerate applications as a service, catering to domains like finance, genomics, and machine learning.

🚀 High-Performance Computing (HPC)

In the realm of high-performance computing, FPGAs are extensively used for tasks like genomics, financial analysis, and pattern searching within government agencies. While the details remain undisclosed due to the sensitive nature of these use cases, FPGAs have proven to be invaluable tools in these domains. Additionally, emerging areas like data analytics and oil and gas are also benefiting from FPGA acceleration.

🏢 Enterprise Segment

In the traditional enterprise segment, companies like insurance firms are adopting FPGAs for their data analytics needs. These solutions seamlessly integrate FPGAs into existing infrastructure, providing Hidden acceleration without the need for extensive FPGA knowledge. This approach allows organizations to leverage the power of FPGAs without the complexities associated with programming them.

🧩 Simplifying FPGA Programming

FPGAs were notorious for their complex programming requirements. However, Intel has been actively working to simplify FPGA programming, opening up opportunities for a broader set of developers. Previously, programming FPGAs involved writing low-level Register Transfer Level (RTL) code. Intel introduced OpenCL as a high-level programming language tailored for Parallel computing, along with various other frameworks. These efforts aim to abstract the FPGA complexity, allowing developers to accelerate applications like data analytics and machine learning without extensive FPGA knowledge.

🔮 The Future of FPGAs

FPGAs have a bright future ahead, thanks to their unmatched flexibility and adaptability. While already being used in diverse scenarios, FPGAs continue to find deployment in exciting new areas.

🌐 Flexibility and Versatility in Deployment

The inherent flexibility of FPGAs enables their deployment in a variety of scenarios. At the recent supercomputing show, Intel showcased the programmable acceleration card, which allows users to quickly switch between machine learning, compression, and genomics tasks. FPGAs can adapt to different requirements and deliver exceptional performance in each use case.

📉 Lower Precision Floating-Point and Machine Learning

Microsoft's recent revelation at the Hot Chips conference highlighted the suitability of 8-bit floating-point precision for machine learning tasks. FPGAs excel in this arena, where they provide almost no loss in scoring accuracy. Thanks to their flexible nature, FPGAs can effortlessly support lower precision floating-point operations, making them an ideal choice for future machine learning advancements.

🆕 New Intel FPGA Family and its Features

Intel has released a newly shipping family of FPGAs manufactured on the 14 nanometer fab. These FPGAs provide significant enhancements over previous generations. For example, Intel showcased impressive gzip and Zee Lib compression speeds of 18 gigabytes per Second using OpenCL. Additionally, Intel demonstrated the ability to offload processing and access storage with nvme over Rocky, which offers accelerated performance for containers and various hypervisors.

🌟 Showcasing FPGA Capabilities

At various events, Intel has demonstrated the impressive capabilities of FPGAs in concrete use cases.

💥 OpenCL Compression

Intel showcased the power of FPGAs in OpenCL compression by achieving an outstanding throughput of 18 gigabytes per second with gzip or Zee Lib. These results highlight the FPGA's ability to accelerate data compression tasks, providing significant performance advantages.

💽 NVMe over Rocky

Intel exhibited a solution featuring nvme over Rocky, effectively offloading processing and storing data using FPGAs. This implementation showcased how FPGAs can accelerate storage-related operations, such as inline compression and encryption. The use of FPGAs in this context allows for enhanced performance and flexibility in different storage environments.

🏁 Conclusion

FPGAs have become an integral part of the data center ecosystem, offering unparalleled acceleration for various workloads. With ongoing efforts to simplify FPGA programming and their inherent flexibility, FPGAs are poised to revolutionize industries ranging from cloud computing to high-performance computing and enterprise applications. Exciting developments such as the adoption of lower precision floating-point and the introduction of new FPGA families by Intel further solidify the future potential of these programmable devices.

Highlights:

• FPGAs play a crucial role in the data center, offering specialized acceleration for diverse applications.
• FPGAs are deployed in the cloud segment, high-performance computing, and the enterprise segment.
• Intel is actively working on simplifying FPGA programming to make them more accessible to developers.
• The future of FPGAs lies in their flexibility, lower precision floating-point support, and new FPGA families.
• Intel has showcased FPGA capabilities in areas such as compression and storage acceleration.

FAQs

Q: What is the role of FPGAs in the data center? A: FPGAs provide high-performance acceleration for specific workloads in the data center, enhancing tasks such as genomics and financial analysis.

Q: Which segments are deploying FPGAs extensively? A: FPGAs are predominantly deployed in the cloud segment, high-performance computing, and the enterprise segment for data analytics purposes.

Q: How has FPGA programming been Simplified? A: Intel has introduced high-level languages like OpenCL, allowing developers to accelerate applications without extensive FPGA knowledge.

Q: What are some future prospects for FPGAs? A: FPGAs offer remarkable flexibility and versatility, making them suitable for diverse deployment scenarios, including lower precision floating-point applications and new FPGA families.

Q: Can FPGAs accelerate data compression and storage operations? A: Yes, FPGAs have demonstrated their capability to accelerate data compression tasks and offload processing for better storage performance using technologies like nvme over Rocky.

Resources:

• Intel HPC Developer Conference: website