Breaking Barriers in Accelerated Computing and Generative AI
Explore the groundbreaking advancements the NVIDIA Blackwell architecture brings to generative AI and accelerated computing. Building upon generations of NVIDIA technologies, Blackwell defines the next chapter in generative AI with unparalleled performance, efficiency, and scale.
Look Inside the Technological Breakthroughs
A New Class of AI Superchip
Blackwell-architecture GPUs pack 208 billion transistors and are manufactured using a custom-built TSMC 4NP process. All Blackwell products feature two reticle-limited dies connected by a 10 terabytes per second (TB/s) chip-to-chip interconnect in a unified single GPU.
Second-Generation Transformer Engine
The second-generation Transformer Engine uses custom Blackwell Tensor Core technology combined with NVIDIA® TensorRT™-LLM and NeMo™ Framework innovations to accelerate inference and training for large language models (LLMs) and Mixture-of-Experts (MoE) models.
To supercharge inference of MoE models, Blackwell Tensor Cores add new precisions, including new community-defined microscaling formats, giving high accuracy and ease of replacement for larger precisions. The Blackwell Transformer Engine utilizes fine-grain scaling techniques called micro-tensor scaling, to optimize performance and accuracy enabling 4-bit floating point (FP4) AI. This doubles the performance and size of next-generation models that memory can support while maintaining high accuracy.
Secure AI
Blackwell includes NVIDIA Confidential Computing, which protects sensitive data and AI models from unauthorized access with strong hardware-based security. Blackwell is the first TEE-I/O capable GPU in the industry, while providing the most performant confidential compute solution with TEE-I/O capable hosts and inline protection over NVIDIA® NVLink®. Blackwell Confidential Computing delivers nearly identical throughput performance compared to unencrypted modes. Enterprises can now secure even the largest models in a performant way, in addition to protecting AI intellectual property (IP) and securely enabling confidential AI training, inference, and federated learning.
NVLink and NVLink Switch
Unlocking the full potential of exascale computing and trillion-parameter AI models hinges on the need for swift, seamless communication among every GPU within a server cluster. The fifth-generation of NVIDIA® NVLink® interconnect can scale up to 576 GPUs to unleash accelerated performance for trillion- and multi-trillion parameter AI models.
The NVIDIA NVLink Switch Chip enables 130TB/s of GPU bandwidth in one 72-GPU NVLink domain (NVL72) and delivers 4X bandwidth efficiency with NVIDIA Scalable Hierarchical Aggregation and Reduction Protocol (SHARP)™ FP8 support. The NVIDIA NVLink Switch Chip supports clusters beyond a single server at the same impressive 1.8TB/s interconnect. Multi-server clusters with NVLink scale GPU communications in balance with the increased computing, so NVL72 can support 9X the GPU throughput than a single eight-GPU system.
Decompression Engine
Data analytics and database workflows have traditionally relied on CPUs for compute. Accelerated data science can dramatically boost the performance of end-to-end analytics, speeding up value generation while reducing cost. Databases, including Apache Spark, play critical roles in handling, processing, and analyzing large volumes of data for data analytics.
Blackwell’s Decompression Engine and ability to access massive amounts of memory in the NVIDIA Grace™ CPU over a high-speed link—900 gigabytes per second (GB/s) of bidirectional bandwidth—accelerate the full pipeline of database queries for the highest performance in data analytics and data science with support for the latest compression formats such as LZ4, Snappy, and Deflate.
Reliability, Availability, and Serviceability (RAS) Engine
Blackwell adds intelligent resiliency with a dedicated Reliability, Availability, and Serviceability (RAS) Engine to identify potential faults that may occur early on to minimize downtime. NVIDIA’s AI-powered predictive-management capabilities continuously monitor thousands of data points across hardware and software for overall health to predict and intercept sources of downtime and inefficiency. This builds intelligent resilience that saves time, energy, and computing costs.
NVIDIA’s RAS Engine provides in-depth diagnostic information that can identify areas of concern and plan for maintenance. The RAS engine reduces turnaround time by quickly localizing the source of issues and minimizes downtime by facilitating effective remediation.