PyTorchCon to showcase warm-start Helion autotuning with shared caches for faster GPU kernel iteration
PyTorch · x · 2026-09-24
PyTorch announced that at PyTorch Conference North America (Oct 20-21, San Jose), Red Hat senior software engineer Alessandro Sangiorgi will present a poster, "Accelerating Helion Autotuning with Warm-Start and Shared Caches."
Helion is a PyTorch DSL for GPU kernels; the talk covers how warm starts let autotuning reuse cached configurations so developers iterate faster instead of repeating cold search runs.
Registration details: standard late tickets $999, academic tickets $249, 25% discount for teams of 10+.
Related event: PyTorchCon to Showcase Helion Autotuning Warm Starts(2 posts)→
More from Infra
- Modal Labs in Talks to Raise at $15 Billion Valuation as Inference Rush Heats Up — nmasc_ · 2026-09-24
- Google paper: 55-70% of quantized LLM cold-start latency is just model loading — rohanpaul_ai · 2026-09-24
- Optical computing for AI debated as veteran cites lack of European interest — IgorCarron · 2026-09-24
- glance-vlm speedlab goes open source: MLX 8-bit cuts local camera VLM latency 27.6% — natesiggard · 2026-09-24
- ClusterMAX 3.0 debuts: comprehensive review of 77 neocloud providers, market view now spans 323 — demian_ai · 2026-09-24
- zlaya: a Zig-based CPU-only inference engine runs Laya on CDN edge via WebAssembly — jedisct1 · 2026-09-24