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docs/kms/IAM.md
- Reduced server startup time. For IAM encryption with the root credentials, MinIO had to use a memory-hard function (Argon2) that (on purpose) consumes a lot of memory and CPU. The new KMS-based approach can use a key derivation function that is orders of magnitudes cheaper w.r.t. memory and CPU. - Root credentials can now be changed easily. Before, a two-step process was required to
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scripts/docs.py
""" update_languages() shutil.rmtree(site_path, ignore_errors=True) langs = [lang.name for lang in get_lang_paths() if lang.is_dir()] cpu_count = os.cpu_count() or 1 process_pool_size = cpu_count * 4 typer.echo(f"Using process pool size: {process_pool_size}") with Pool(process_pool_size) as p: p.map(build_lang, langs) @app.command()
Python - Registered: Sun May 05 07:19:11 GMT 2024 - Last Modified: Mon Jan 22 19:26:14 GMT 2024 - 10.9K bytes - Viewed (1) -
ci/official/envs/macos_x86
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=macos_x86 TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_INDEX_HTML_ENABLE=1 TFCI_LIB_SUFFIX="-cpu-darwin-x86_64" TFCI_MACOS_BAZEL_TEST_DIR_ENABLE=1 TFCI_MACOS_BAZEL_TEST_DIR_PATH="/System/Volumes/Data/bazel_output" TFCI_MACOS_INSTALL_BAZELISK_ENABLE=1
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docs/de/docs/deployment/docker.md
Die **Anzahl der Prozesse** auf diesem Image wird **automatisch** anhand der verfügbaren CPU-**Kerne** berechnet. Das bedeutet, dass versucht wird, so viel **Leistung** wie möglich aus der CPU herauszuquetschen. Sie können das auch in der Konfiguration anpassen, indem Sie **Umgebungsvariablen**, usw. verwenden.
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docs/en/docs/deployment/docker.md
The **number of processes** on this image is **computed automatically** from the CPU **cores** available. This means that it will try to **squeeze** as much **performance** from the CPU as possible. You can also adjust it with the configurations using **environment variables**, etc. But it also means that as the number of processes depends on the CPU the container is running, the **amount of memory consumed** will also depend on that.
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docs/pt/docs/deployment/docker.md
O **número de processos** nesta imagem é **calculado automaticamente** a partir dos **núcleos de CPU** disponíveis. Isso significa que ele tentará **aproveitar** o máximo de **desempenho** da CPU possível. Você também pode ajustá-lo com as configurações usando **variáveis de ambiente**, etc. Mas isso também significa que, como o número de processos depende da CPU do contêiner em execução, a **quantidade de memória consumida** também dependerá disso.
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guava/src/com/google/common/collect/CompactLinkedHashMap.java
* java.util.LinkedHashMap}. Generally speaking, this class reduces object allocation and memory * consumption at the price of moderately increased constant factors of CPU. Only use this class * when there is a specific reason to prioritize memory over CPU. * * @author Louis Wasserman */ @J2ktIncompatible // no support for access-order mode in LinkedHashMap delegate @GwtIncompatible // not worth using in GWT for now
Java - Registered: Fri Apr 05 12:43:09 GMT 2024 - Last Modified: Mon Apr 01 16:15:01 GMT 2024 - 10.2K bytes - Viewed (0) -
ci/official/envs/linux_x86_tpu
# ============================================================================== source ci/official/envs/linux_x86 TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_cpu_linux --config=tpu" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_tpu TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_tpu" TFCI_LIB_SUFFIX="-tpu-linux-x86_64" TFCI_WHL_BAZEL_TEST_ENABLE=0
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guava/src/com/google/common/collect/CompactLinkedHashSet.java
* java.util.LinkedHashSet}. Generally speaking, this class reduces object allocation and memory * consumption at the price of moderately increased constant factors of CPU. Only use this class * when there is a specific reason to prioritize memory over CPU. * * @author Louis Wasserman */ @GwtIncompatible // not worth using in GWT for now @ElementTypesAreNonnullByDefault
Java - Registered: Fri Apr 05 12:43:09 GMT 2024 - Last Modified: Mon Feb 05 21:38:59 GMT 2024 - 9.7K bytes - Viewed (0) -
ci/official/envs/macos_arm64
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=macos_arm64 TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_INDEX_HTML_ENABLE=1 TFCI_LIB_SUFFIX="-cpu-darwin-arm64" TFCI_MACOS_BAZEL_TEST_DIR_ENABLE=1 TFCI_MACOS_BAZEL_TEST_DIR_PATH="/Volumes/BuildData/bazel_output" TFCI_OUTPUT_DIR=build_output TFCI_WHL_BAZEL_TEST_ENABLE=1 TFCI_WHL_SIZE_LIMIT=240M
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