…Benchmarking AI Systems: from Model Metrics to Real-World Performance The agentic AI stack has evolved to fast multi-model orchestration, tool-augmented reasoning, and long-running inference chains. The hardware conversation…
…5 (default) The same hardware, operating system, Picard version, and input dataset were used for all benchmark runs to ensure a fair comparison. Practical Takeaways Profiling and benchmark results show that AMD…
…NPUEval NPUEval is an LLM evaluation dataset designed to target AIE kernel code generation on Ryzen™ AI hardware, enabling accurate benchmarking of NPU-focused models. Omnistat Omnistat offers utilities for aggregating scale…
…Benchmarking AI Systems: from Model Metrics to Real-World Performance The agentic AI stack has evolved to fast multi-model orchestration, tool-augmented reasoning, and long-running inference chains. The hardware conversation…
…Verification Kernel benchmark. Kernel benchmark plus end-to-end serving benchmark. Knowledge base RAG-style knowledge base and reverse knowledge. perf_knowledge: structured kernel optimization knowledge across operators, backends, GPU generations, dtypes…
…Benchmarking AI Systems: from Model Metrics to Real-World Performance The agentic AI stack has evolved to fast multi-model orchestration, tool-augmented reasoning, and long-running inference chains. The hardware conversation…
…When we compared the official data on the SPECint benchmarks, the 4th Gen AMD EPYC Server CPU was the best processor we could get.” Deutsche Telekom needed a strong hardware vendor partnership…
In this post, we describe how we pushed GPU-based simulation to its limits, running what we believe to be the largest single-GPU universal quantum simulations to date on AMD hardware…
…raise FileNotFoundError(f"benchmark_test.txt not found: {benchmark_path}") with open(benchmark_path, "r", encoding="utf-8") as f: benchmark_text = f.read() # --- Phase 1: tokenize file only; take fixed slices…
…Unlocking AMD Hardware for Scalable LLM Serving Jun 15, 2026 Large language model serving is moving from single-engine optimization to full-stack distributed inference. Production deployments must handle high concurrency, long…