{"schema_version":"onlylabs.public_signal.v1","title":"NVIDIA Repo: NVIDIA/numba-cuda-mlir","description":"NVIDIA repo signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/4cf82f99-32b5-4a75-aa43-ea16238d2815","json_url":"https://onlylabs.fyi/signals/4cf82f99-32b5-4a75-aa43-ea16238d2815/signal.json","generated_at":"2026-06-11T02:51:41.149315+00:00","org":{"slug":"nvidia","name":"NVIDIA","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/nvidia","dossier_json_url":"https://onlylabs.fyi/labs/nvidia/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/4cf82f99-32b5-4a75-aa43-ea16238d2815","signal_json":"https://onlylabs.fyi/signals/4cf82f99-32b5-4a75-aa43-ea16238d2815/signal.json","source":"https://github.com/NVIDIA/numba-cuda-mlir","lab_dossier":"https://onlylabs.fyi/labs/nvidia","lab_dossier_json":"https://onlylabs.fyi/labs/nvidia/dossier.json","analysis":"https://onlylabs.fyi/analysis/nvidia","analysis_json":"https://onlylabs.fyi/analysis/nvidia/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/nvidia/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":null,"topic_signals_json":null,"topic_feed":null,"data_business":null},"answer_pack":{"answer":"NVIDIA published NVIDIA/numba-cuda-mlir (Python). 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It is evolved from [Numba-CUDA](https://github.com/NVIDIA/numba-cuda), and is intended to be compatible with Numba-CUDA kernels. Numba-CUDA-MLIR aims to interoperate well with existing programming models whilst also allowing experts sufficient control over code generation. Quick Start Install with pip: ``` pip install numba-cuda-mlir[cu13] # or [cu12] if using CUDA 12 ``` Writing and executing a simple vector add kernel: ```python import numpy as np from numba_cuda_mlir import cuda @cuda.jit def vector_add(a, b, out): i = cuda.grid(1) if i < out.shape[0]: out[i] = a[i] + b[i] n = 1_000_000 a = np.ones(n, dtype=np.float32) b = np.ones(n, dtype=np.float32) out = np.zeros(n, dtype=np.float32) threads_per_block = 256 blocks = (n + threads_per_block - 1) // threads_per_block vector_add[blocks, threads_per_block](a, b, out) ``` Migration from Numba /..."},"evidence_pages":[{"url":"https://github.com/NVIDIA/numba-cuda-mlir","final_url":"https://github.com/NVIDIA/numba-cuda-mlir","title":"NVIDIA/numba-cuda-mlir repository metadata","http_status":200,"content_type":"application/json","capture_method":"plain","fetched_at":"2026-06-11T02:51:41.149315+00:00","bytes":11674,"raw_path":"9681bec88f4cef46a8c95ece88d9852eeaf37301c9201ef5d28efe64ba4e0704.json","content_hash":"b89351eaac64241dd7349943807e8546bd5dc400290b7ddf7429f63527db98e2","excerpt_chars":1200,"truncated":true,"excerpt":"NVIDIA/numba-cuda-mlir Description: repo for Numba-CUDA-MLIR Language: Python License: Apache-2.0 Stars: 32 Forks: 14 Open issues: 33 Created: 2026-04-15T16:36:34Z Pushed: 2026-06-11T00:58:24Z Default branch: main Fork: no Archived: no README: Numba-CUDA-MLIR Numba-CUDA-MLIR provides a programming model similar to CUDA C++ in Python. 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Quick Start Install with pip: ``` pip install numba-cuda-mlir[cu13] # or [cu12] if using CUDA 12 ``` Writing and executing a simple vector add kernel: ```python import numpy as np from numba_cuda_mlir import cuda @cuda.jit def vector_add(a, b, out): i = cuda.grid(1) if i < out.shape[0]: out[i] = a[i] + b[i] n = 1_000_000 a = np.ones(n, dtype=np.float32) b = np.ones(n, dtype=np.float32) out = np.zeros(n, dtype=np.float32) threads_per_block = 256 blocks = (n + threads_per_block - 1) // threads_per_block vector_add[blocks, threads_per_block](a, b, out) ``` Migration from Numba /..."}],"related_signals":[{"id":"9c2bf9a4-d1d1-40d5-82e6-f8f753666e51","url":"https://onlylabs.fyi/signals/9c2bf9a4-d1d1-40d5-82e6-f8f753666e51","source_url":"https://github.com/NVIDIA/srt-slurm-recipes","title":"NVIDIA/srt-slurm-recipes","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"nvidia","name":"NVIDIA","category":"frontier-lab"},"occurred_at":"2026-06-06T16:27:18+00:00","first_seen_at":"2026-06-09T07:00:17.261926+00:00","date_source":"source"},{"id":"69994713-c7b8-497a-9632-f22a985e3ab2","url":"https://onlylabs.fyi/signals/69994713-c7b8-497a-9632-f22a985e3ab2","source_url":"https://github.com/NVIDIA/instant-nurec","title":"NVIDIA/instant-nurec","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"nvidia","name":"NVIDIA","category":"frontier-lab"},"occurred_at":"2026-05-22T18:08:59+00:00","first_seen_at":"2026-06-05T20:58:43.255815+00:00","date_source":"source"},{"id":"8e495175-9ea0-4970-8f0c-bce8e6eeddbb","url":"https://onlylabs.fyi/signals/8e495175-9ea0-4970-8f0c-bce8e6eeddbb","source_url":"https://github.com/NVIDIA/nv-config-manager","title":"NVIDIA/nv-config-manager","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"nvidia","name":"NVIDIA","category":"frontier-lab"},"occurred_at":"2026-05-21T20:26:37+00:00","first_seen_at":"2026-06-05T20:58:43.255815+00:00","date_source":"source"},{"id":"20d352e8-82e7-477b-8bdf-923812420180","url":"https://onlylabs.fyi/signals/20d352e8-82e7-477b-8bdf-923812420180","source_url":"https://github.com/NVIDIA/nurec-skills","title":"NVIDIA/nurec-skills","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"nvidia","name":"NVIDIA","category":"frontier-lab"},"occurred_at":"2026-05-20T18:40:04+00:00","first_seen_at":"2026-06-05T20:58:43.255815+00:00","date_source":"source"},{"id":"9ea31493-953e-4b1e-bdf1-e116d282f650","url":"https://onlylabs.fyi/signals/9ea31493-953e-4b1e-bdf1-e116d282f650","source_url":"https://github.com/NVIDIA/cosmos-framework","title":"NVIDIA/cosmos-framework","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"nvidia","name":"NVIDIA","category":"frontier-lab"},"occurred_at":"2026-05-19T16:27:26+00:00","first_seen_at":"2026-06-05T20:58:43.255815+00:00","date_source":"source"},{"id":"6d0e432a-4b75-4cda-880e-54189f717d5b","url":"https://onlylabs.fyi/signals/6d0e432a-4b75-4cda-880e-54189f717d5b","source_url":"https://github.com/NVIDIA/harmonizer","title":"NVIDIA/harmonizer","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"nvidia","name":"NVIDIA","category":"frontier-lab"},"occurred_at":"2026-05-19T15:39:32+00:00","first_seen_at":"2026-06-05T20:58:43.255815+00:00","date_source":"source"}]}