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RsimdDispatch uses a single R shared library. All
compiled variants are linked into that shared object, and a function
pointer selects the active implementation.
This means backend switching is safe in one R process:
library(RsimdDispatch)
x <- as.raw(c(0, 1, 2, 3))
simd_set_backend("scalar")
count_nonzero(x)
#> [1] 3
candidate <- setdiff(simd_info()$available_backends, "scalar")[1]
if (!is.na(candidate)) {
simd_set_backend(candidate)
count_nonzero(x)
}
#> [1] 3
simd_set_backend("auto")
simd_backend()
#> [1] "avx2"simd_set_backend() performs two checks for explicit
choices:
There is intentionally no unsafe force mode. If a backend is not available, the setter errors before any SIMD-only instruction can execute.
simd_info()[c("compiled_backends", "cpu_supported_backends", "available_backends")]
#> $compiled_backends
#> [1] "scalar" "sse2" "sse41" "avx2" "avx512"
#>
#> $cpu_supported_backends
#> [1] "scalar" "sse2" "sse41" "avx2"
#>
#> $available_backends
#> [1] "scalar" "sse2" "sse41" "avx2"The SIMD source files use SIMDe types and functions, but the backend
names refer to native target-specific staged kernel objects. During
configuration, each optional backend is accepted only if the compiler
flag and SIMDe header together define the expected native SIMDe macro.
For example, the AVX2 probe compiles with -mavx2, includes
<simde/x86/avx2.h>, and requires
SIMDE_X86_AVX2_NATIVE. AVX-512 similarly requires the
native F, BW, and VL macros.
Those flags make the compiler define target macros such as
__AVX2__ or __AVX512BW__. SIMDe maps those to
SIMDE_ARCH_* and then to SIMDE_*_NATIVE; the
SIMDe function bodies use native intrinsics under those macros and fall
back only when the native macro is absent. The generated
src/Makevars links the staged objects into the package
shared library while the dispatcher, CPU feature detection, and R API
are compiled by R’s ordinary src/Makevars path.
The installed diagnostics report the backends that passed the SIMDe-native compile probe:
simd_info()[c("compiled_backends", "simde_native_backends", "simde_version", "simde_commit")]
#> $compiled_backends
#> [1] "scalar" "sse2" "sse41" "avx2" "avx512"
#>
#> $simde_native_backends
#> [1] "sse2" "sse41" "avx2" "avx512"
#>
#> $simde_version
#> [1] "0.8.4"
#>
#> $simde_commit
#> [1] "f3e8262173b7089db9a9d57a9ecef8dd07ad9c97"The following benchmark is evaluated when this article is built. It uses a small input so package checks remain fast, but it still exercises same-process backend switching through the public API.
if (requireNamespace("bench", quietly = TRUE)) {
bench_x <- rep(as.raw(c(0, 1, 2, 3, 0, 255, 7, 0)), length.out = 2^20)
bench <- bench::mark(
scalar = {
simd_set_backend("scalar")
count_nonzero(bench_x)
},
auto = {
simd_set_backend("auto")
count_nonzero(bench_x)
},
iterations = 5,
check = TRUE
)
simd_set_backend("auto")
bench[, c("expression", "median", "itr/sec", "n_itr")]
}
#> # A tibble: 2 × 3
#> expression median `itr/sec`
#> <bch:expr> <bch:tm> <dbl>
#> 1 scalar 235.5µs 4309.
#> 2 auto 32.1µs 21184."auto" selects the best backend from the compiled and
supported intersection. The current ranking is:
avx512 > avx2 > sse41 > sse2 > neon > scalarArchitecture guards mean x86 systems normally consider x86 backends and ARM systems normally consider NEON. Scalar is always available.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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