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Cargo.lock

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Cargo.toml

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@@ -82,7 +82,7 @@ spin = { version = "0.9.8", features = [
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strum = "0.26.3"
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strum_macros = "0.26.4"
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syn = { version = "2.0.74", features = ["full", "extra-traits"] }
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tempfile = "3.11.0"
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tempfile = "3.12.0"
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thiserror = "1.0.61"
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tokio = { version = "1.39.2", features = ["rt", "macros"] }
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tracing-appender = "0.2.3"
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"std_rng",
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] } # std_rng is for no_std
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rand_distr = { version = "0.4.3", default-features = false }
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serde = { version = "1.0.206", default-features = false, features = [
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serde = { version = "1.0.208", default-features = false, features = [
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"derive",
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"alloc",
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] } # alloc is for no_std, derive is needed
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serde_json = { version = "1.0.124", default-features = false }
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uuid = { version = "1.9.1", default-features = false }
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libc = "0.2.155"
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libc = "0.2.157"
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tch = "0.15.0"
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nvml-wrapper = "0.10.0"
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sysinfo = "0.30.13"

README.md

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@@ -155,7 +155,7 @@ Hardware specific features 🔥
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</summary>
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<br />
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It is no secret that deep learning is mosly relying on matrix multiplication as its core operation,
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It is no secret that deep learning is mostly relying on matrix multiplication as its core operation,
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since this is how fully-connected neural networks are modeled.
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More and more, hardware manufacturers optimize their chips specifically for matrix multiplication

backend-comparison/README.md

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By default `burnbench` uses a compact output with a progress bar which hides the
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compilation logs and benchmarks results as they are executed. If a benchmark
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failed to run, the `--verbose` flag can be use to investigate the error.
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failed to run, the `--verbose` flag can be used to investigate the error.
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#### Authentication and benchmarks sharing
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burn-book/book.toml

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@@ -12,3 +12,6 @@ language = "en"
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multilingual = false
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src = "src"
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title = "The Burn Book 🔥"
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[output.html]
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mathjax-support = true

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