Tech Meridian ← ENTITY INDEX
PROMY MERIDIAN RU

COMPANY · ENTITY #6970

Triton

Related event timeline, sources and context from the news index.

EVENT TIMELINE

2

MODELS · 1 SOURCE · AWS Machine Learning

i14 trains and serves Laplace 3B linear-attention model on AWS Trainium2 with TorchNeuron Native

i14 ported its Laplace 3B 3B-parameter linear-attention decoder (using Gated Linear Attention and a fixed 29.5 MB recurrent state) to AWS Trainium2 via TorchNeuron Native and native PyTorch operators. On a trn2.48xlarge instance the team reported ~120,000 training tokens/sec and serving throughput of 11,544 output tokens/sec across 1,280 concurrent sequences after replacing a Triton kernel, optimizing MuonFSDP2 collectives, and statically unrolling the GLA recurrence for the Trainium2 compiler.

7.0

CODING · 1 SOURCE · InfoQ AI, ML & Data Engineering

Google adds cycle-level kernel profiling to XProf for TPU v7

Google added a Kernel Profiling suite to XProf (the OpenXLA/JAX profiler), exposing cycle-level details for custom kernels (e.g., Pallas) and sampling hardware performance counters on TPU v7 (Ironwood). The tooling shows lowered MLIR, per-unit time-aligned counter tracks, a Perf Counters view with ~16,000 raw counters, and supports periodic sampling (1µs floor) or external-triggered sub-microsecond capture; a Google demo using triple buffering reduced a matmul kernel from 125.5µs to 88µs.

6.0