Teledyne LeCroy Summit analyzers, exercisers, jammers,
interposers, and test systems help build and optimize the fastest and
latest systems using PCIe to support AI. These devices and computing
systems use the high-speed interface that connects AI accelerators, such
as GPUs and custom silicon chips, to the central processing unit (CPU).
Its continuous evolution ensures that AI systems remain at the cutting
edge of technology, ready to meet the challenges of tomorrow’s
data-driven world.
- Scalability: With each new generation, PCIe doubles its
bandwidth, accommodating the growing demands of AI applications. The
latest PCIe 6.0 specification offers a data transfer rate of 64 GT/s
per pin, ensuring that AI systems can handle increasingly complex
tasks.
- Versatility: PCIe is used in various form factors, from large
chips for deep-learning systems to smaller, spatial accelerators
that can be scaled up to process extensive neural networks requiring
hundreds of petaFLOPS of processing power.
- Energy Efficiency: Newer PCIe versions introduce low-power
states, contributing to greater power efficiency in AI systems. This
is essential for sustainable and cost-effective AI operations.
- Interconnectivity: PCIe facilitates the interconnection of
compute, accelerators, networking, and storage devices within AI
infrastructure, enabling efficient data center solutions with lower
power consumption and maximum reach.
CXL holds significant promise in shaping the landscape of AI
and Teledyne LeCroy solutions are the only way to test and optimize
today’s CXL systems. Memory efficiency, latency reduction, and
performance are all achieved using Teledyne LeCroy solutions supporting
CXL testing and compliance - all crucial for maintaining low latency and
high throughput. This is especially important for bandwidth-intensive AI
workloads that require quick access to large datasets.
- Memory Capacity Expansion: CXL allows connecting a large
memory pool to multiple processors or accelerators. This is crucial
for AI/HPC applications dealing with massive datasets.
- Reduced Latency: CXL’s low-latency design ensures data
travels quickly between compute elements. AI/ML workloads benefit
from minimized wait times.
- Interoperability: CXL promotes vendor-neutral compatibility,
allowing different accelerators and memory modules to work
seamlessly together.
- Enhanced Memory Bandwidth: CXL significantly improves memory
bandwidth, ensuring data-intensive workloads access data without
bottlenecks.
