Leading us into a new era of powerful computers, NVIDIA has unveiled the groundbreaking NVIDIA Blackwell platform, poised to transform the landscape of technological innovation. This cutting-edge advancement empowers enterprises worldwide to seamlessly construct and operate real-time generative AI on trillion-parameter large language models, all while significantly reducing costs and energy consumption by up to 25 times compared to its forerunner.
An Overview of the NVIDIA Blackwell Platform
The Blackwell GPU architecture incorporates six innovative technologies tailored for accelerated computing, poised to unlock advancements in various fields including data processing, engineering simulation, electronic design automation, computer-aided drug design, quantum computing, and generative AI—emerging opportunities for NVIDIA across industries.
Jensen Huang, NVIDIA’s founder and CEO, emphasized the company’s three-decade pursuit of accelerated computing aimed at enabling transformative breakthroughs such as deep learning and AI. He highlighted generative AI as the defining technology of our era, with Blackwell positioned as the engine driving this new industrial revolution. Collaboration with leading global companies is anticipated to realize AI’s potential across diverse sectors.
Notable entities expected to embrace Blackwell include Amazon Web Services, Dell Technologies, Google, Meta, Microsoft, OpenAI, Oracle, Tesla, and xAI, underscoring its broad appeal and anticipated impact across the tech landscape.
Introducing a New Era: The AI Superchip Redefining Computational Power
The Blackwell-architecture GPUs contain an impressive 208 billion transistors and are crafted using a specialized TSMC 4NP manufacturing process. Each Blackwell product boasts two reticle-limited dies linked by a 10 terabytes per second (TB/s) chip-to-chip interconnect, all integrated into a single GPU unit.
The Next Leap: Second-Generation Transformer Engine
The second iteration of the Transformer Engine leverages proprietary Blackwell Tensor Core technology in conjunction with NVIDIA® TensorRT™-LLM and NeMo™ Framework advancements to expedite both inference and training processes for large language models (LLMs) and Mixture-of-Experts (MoE) models.
In enhancing the inference capabilities of MoE models, Blackwell Tensor Cores introduce novel precisions, including newly defined microscaling formats by the community. These formats offer heightened accuracy and simplified replacement for larger precisions. Moreover, the Blackwell Transformer Engine implements fine-grained scaling methodologies termed micro-tensor scaling, optimizing both performance and accuracy to enable 4-bit floating-point (FP4) AI. This advancement doubles the performance and accommodates larger next-generation models within the memory constraints while upholding superior accuracy.
Secure AI: NVIDIA Confidential Computing
Blackwell incorporates NVIDIA Confidential Computing, a feature designed to safeguard sensitive data and AI models against unauthorized access through robust hardware-based security measures. Distinguished as the industry’s first TEE-I/O capable GPU, Blackwell offers the most efficient confidential compute solution, boasting TEE-I/O capable hosts and inline protection via NVIDIA® NVLink®. Remarkably, Blackwell Confidential Computing maintains nearly identical throughput performance compared to unencrypted modes. This advancement empowers enterprises to secure even the most extensive models effectively, safeguarding AI intellectual property (IP) and facilitating secure operations such as confidential AI training, inference, and federated learning.
Discover Deeper Insights into NVIDIA Confidential Computing
Sam Altman, CEO of OpenAI: “Blackwell offers massive performance leaps, and will accelerate our ability to deliver leading-edge models. We’re excited to continue working with NVIDIA to enhance AI compute.”
NVLink and NVLink Switch Powerhouse
To fully harness the power of exascale computing and trillion-parameter AI models, seamless communication among GPUs within server clusters is paramount. Enter the fifth-generation NVIDIA® NVLink® interconnect, capable of scaling up to 576 GPUs, unleashing unprecedented performance for trillion- and multi-trillion parameter AI models.
The NVIDIA NVLink Switch Chip facilitates an impressive 130TB/s of GPU bandwidth within a single 72-GPU NVLink domain (NVL72). With support for NVIDIA Scalable Hierarchical Aggregation and Reduction Protocol (SHARP)™ FP8, it achieves 4X bandwidth efficiency. Moreover, the NVLink Switch Chip extends its capabilities to clusters beyond a single server, maintaining an impressive 1.8TB/s interconnect. Multi-server clusters equipped with NVLink exponentially scale GPU communications, enabling the NVL72 to support 9X the GPU throughput compared to a single eight-GPU system.
Dive Deeper into NVIDIA NVLink and NVLink Switch
Marvel Decompression Engine
Traditionally, data analytics and database operations have heavily relied on CPUs for computation. However, the integration of accelerated data science can revolutionize this landscape, significantly enhancing the efficiency of end-to-end analytics processes. This acceleration not only expedites value generation but also contributes to cost reduction. Databases like Apache Spark are pivotal in managing, processing, and analyzing vast datasets for data analytics purposes.
Blackwell introduces its Decompression Engine, coupled with the remarkable capability to tap into extensive memory resources within the NVIDIA Grace™ CPU through a high-speed link—offering an impressive 900 gigabytes per second (GB/s) of bidirectional bandwidth. This integration accelerates the entire database query pipeline, ensuring optimal performance for data analytics and data science tasks. Moreover, Blackwell supports cutting-edge compression formats such as LZ4, Snappy, and Deflate, further enhancing its capabilities in data processing and analysis.
Magnificent Reliability, Availability, and Serviceability (RAS) Engine
Blackwell introduces an innovative approach to resilience with its dedicated Reliability, Availability, and Serviceability (RAS) Engine, aimed at proactively identifying potential faults to mitigate downtime effectively. Leveraging NVIDIA’s AI-driven predictive management capabilities, this system continuously monitors a plethora of data points spanning both hardware and software realms to predict and intercept potential sources of downtime and inefficiency. The result? A robust framework of intelligent resilience that not only saves time and energy but also slashes computing costs.
At the heart of NVIDIA’s RAS Engine lies its ability to furnish comprehensive diagnostic insights, enabling the identification of potential problem areas and facilitating proactive maintenance planning. By swiftly pinpointing the root cause of issues, the RAS Engine significantly reduces turnaround time for issue resolution and minimizes downtime, thereby ensuring uninterrupted operations and optimizing efficiency.
Conclusion
NVIDIA’s Blackwell architecture represents a quantum leap in the realm of generative AI and accelerated computing. By harnessing the collective power of cutting-edge NVIDIA technologies, Blackwell ushers in a new era characterized by unprecedented performance, efficiency, and scalability. With its groundbreaking advancements, Blackwell sets the stage for transformative innovations and paves the way for monumental progress in the field of artificial intelligence.
