by Evgenii Dushkin, Ryan Malone, Maryam Tahhan | Sep 28, 2026 | AI
Deploying large language models (LLMs) on enterprise hardware requires a balance of reproducibility, security, and performance. Accurately benchmarking model performance under production-like workloads is both challenging and crucial for optimizing infrastructure...
by Maryam Tahhan, John Harrigan, Anton Ivanov, Paul Power, Luigi Mario Zuccarelli | May 28, 2026 | AI
As enterprises look to optimize the total cost of ownership (TCO) of Large Language Model deployment, utilizing existing enterprise CPU infrastructure alongside GPU resources for specific inference workloads has become a strategic initiative. However, infrastructure...
by Anton Ivanov, Maryam Tahhan | Feb 5, 2026 | AI
Triton is a domain-specific language and compiler for writing high-performance GPU kernels (snippets of compiled GPU code) using a Python-like syntax. It offers fine-grained control over memory and parallelism, making it ideal for custom, architecture-optimized...
by Maryam Tahhan | Jan 29, 2026 | AI
Triton is a domain-specific language and compiler for writing high-performance GPU kernels in Python. It offers fine-grained control over memory and parallelism, making it ideal for custom, architecture-optimized compute in machine language and high-performance...
by Maryam Tahhan | Mar 20, 2025 | AI
The Triton project from OpenAI is at the forefront of a groundbreaking movement to democratize AI accelerators and GPU kernel programming. It provides a powerful and flexible framework for writing high performance GPU kernels. As AI workloads become increasingly...
