How Agentic AI Is Reshaping Chip Design
…Agentic AI is a much better fit for that reality than a simple chatbot model. Why This Matters in Semiconductor Design Chip design is one of the clearest examples of where this…
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How To: Migrate your Cloud Instance to AMD EPYC
…It focuses on two common deployment models: Virtual machine (VM) based workloads Containerized workloads in Kubernetes clusters Key considerations Most successful migrations follow the same pattern: confirm compatibility, prepare a clean base…
AMD Instinct™ AI & HPC Software Ecosystem
…Liquid AI Liquid AI partners with AMD to support advanced AI model architectures designed for efficient training and inference on AMD Instinct™ GPUs. By combining innovative foundation model design with AMD accelerated…
A progressive approach to accelerating system-level verification for AMD Versal™ adaptive SoC designs
…This flow combines several independent simulators to model the major subsystems of a Versal device. In a typical hardware emulation verification, the processing system is simulated using QEMU, the PL is simulated…
Advancing Technology, Sustaining the Future
…inference by 2030, from a 2024 base year. 8 Our new 2030 rack-level energy efficiency goal has major implications for equipment consolidation. Using training of a typical AI model in 2025…
Learning Velocity, Trust, and the Future of the AI PC at Work
…Future AI deployments are expected to increasingly use hybrid models, which split processing between local devices and cloud environments. AI is changing where compute happens and AMD iis focused on understanding our…
Compute Defines Scale: How MediaKind and AMD Are Rethinking Video Infrastructure from On‑Prem to Cloud
…MediaKind‑modeled deployment scenarios show that consolidating software‑defined video workloads on EPYC CPU‑based servers can substantially reduce physical headend footprint, depending on workload mix, redundancy requirements, and codec profiles. These…
Advancing Together: How 2025 Shaped Our Path Forward
…This release provides a significant performance lift over previous generations and supports the latest models, algorithms, and hardware. 2 Our goal with ROCm 7 is simple: make it easier and faster for…
Reliable SHA-256 Through LLM-Aided HLS Dataflow Optimization
…compressing hours of documentation reading and mental modeling into a single interaction. The LLM produced synthesizable code at roughly 80% first-attempt correctness . The generated code was structurally sound, with correct stream…
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