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| Components | Container | Build | Test |
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ghcr.io/nvidia/jax:base
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ghcr.io/nvidia/jax:jax
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ghcr.io/nvidia/jax:levanter
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ghcr.io/nvidia/jax:equinox
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ghcr.io/nvidia/jax:triton
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ghcr.io/nvidia/jax:upstream-t5x
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ghcr.io/nvidia/jax:t5x
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ghcr.io/nvidia/jax:upstream-pax
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ghcr.io/nvidia/jax:pax
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ghcr.io/nvidia/jax:maxtext
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ghcr.io/nvidia/jax:grok
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ghcr.io/nvidia/jax:gemma
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In all of the above cases, ghcr.io/nvidia/jax:XXX points to the most recent
nightly build of the container for XXX. These containers are also tagged as
ghcr.io/nvidia/jax:XXX-YYYY-MM-DD, if a stable reference is required.
This repo currently hosts a public CI for JAX on NVIDIA GPUs and covers some JAX libraries like: T5x, PAXML, Transformer Engine, Pallas and others to come soon.
We currently enable training and evaluation for the following models:
| Model Name | Pretraining | Fine-tuning | Evaluation |
|---|---|---|---|
| GPT-3(paxml) | ✔️ | ✔️ | |
| LLaMA2(paxml) | ✔️ | ||
| t5(t5x) | ✔️ | ✔️ | ✔️ |
| ViT | ✔️ | ✔️ | ✔️ |
| Imagen | ✔️ | ✔️ | |
| PaliGemma | ✔️ | ✔️ |
We will update this table as new models become available, so stay tuned.
The JAX image is embedded with the following flags and environment variables for performance tuning:
| XLA Flags | Value | Explanation |
|---|---|---|
--xla_gpu_enable_latency_hiding_scheduler |
true |
allows XLA to move communication collectives to increase overlap with compute kernels |
--xla_gpu_enable_triton_gemm |
false |
use cuBLAS instead of Trition GeMM kernels |
| Environment Variable | Value | Explanation |
|---|---|---|
CUDA_DEVICE_MAX_CONNECTIONS |
1 |
use a single queue for GPU work to lower latency of stream operations; OK since XLA already orders launches |
NCCL_NVLS_ENABLE |
0 |
Disables NVLink SHARP (1). Future releases will re-enable this feature. |
CUDA_MODULE_LOADING |
EAGER |
Disables lazy-loading (1) which uses slightly more GPU memory. |
There are various other XLA flags users can set to improve performance. For a detailed explanation of these flags, please refer to the GPU performance doc. XLA flags can be tuned per workflow. For example, each script in contrib/gpu/scripts_gpu sets its own XLA flags.
See this page for more information about how to profile JAX programs on GPU.
`bus error` when running JAX in a docker container
Solution:
docker run -it --shm-size=1g ...Explanation:
The bus error might occur due to the size limitation of /dev/shm. You can address this by increasing the shared memory size using
the --shm-size option when launching your container.
enroot/pyxis reports error code 404 when importing multi-arch images
Problem description:
slurmstepd: error: pyxis: [INFO] Authentication succeeded
slurmstepd: error: pyxis: [INFO] Fetching image manifest list
slurmstepd: error: pyxis: [INFO] Fetching image manifest
slurmstepd: error: pyxis: [ERROR] URL https://ghcr.io/v2/nvidia/jax/manifests/<TAG> returned error code: 404 Not Found
Solution: Upgrade enroot or apply a single-file patch as mentioned in the enroot v3.4.0 release note.
Explanation: Docker has traditionally used Docker Schema V2.2 for multi-arch manifest lists but has switched to using the Open Container Initiative (OCI) format since 20.10. Enroot added support for OCI format in version 3.4.0.
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