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miri: implement most floating point math operations using soft floats #3969

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miri: implement most floating point math operations using soft floats #3969

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36 changes: 31 additions & 5 deletions Cargo.lock
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1 change: 1 addition & 0 deletions Cargo.toml
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Expand Up @@ -27,6 +27,7 @@ ctrlc = "3.2.5"
chrono = { version = "0.4.38", default-features = false }
chrono-tz = "0.10"
directories = "5"
fpmath = { version = "0.1.1", features = ["soft-float"] }

# Copied from `compiler/rustc/Cargo.toml`.
# But only for some targets, it fails for others. Rustc configures this in its CI, but we can't
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62 changes: 24 additions & 38 deletions src/intrinsics/mod.rs
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Expand Up @@ -202,21 +202,18 @@ pub trait EvalContextExt<'tcx>: crate::MiriInterpCxExt<'tcx> {
=> {
let [f] = check_arg_count(args)?;
let f = this.read_scalar(f)?.to_f32()?;
// Using host floats (but it's fine, these operations do not have guaranteed precision).
let f_host = f.to_host();
let res = match intrinsic_name {
"sinf32" => f_host.sin(),
"cosf32" => f_host.cos(),
"sqrtf32" => f_host.sqrt(), // FIXME Using host floats, this should use full-precision soft-floats
"expf32" => f_host.exp(),
"exp2f32" => f_host.exp2(),
"logf32" => f_host.ln(),
"log10f32" => f_host.log10(),
"log2f32" => f_host.log2(),
let op = match intrinsic_name {
"sinf32" => math::UnaryOp::Sin,
"cosf32" => math::UnaryOp::Cos,
"sqrtf32" => math::UnaryOp::Sqrt,
"expf32" => math::UnaryOp::Exp,
"exp2f32" => math::UnaryOp::Exp2,
"logf32" => math::UnaryOp::Ln,
"log10f32" => math::UnaryOp::Log10,
"log2f32" => math::UnaryOp::Log2,
_ => bug!(),
};
let res = res.to_soft();
let res = this.adjust_nan(res, &[f]);
let res = math::unary_op(this, op, f);
this.write_scalar(res, dest)?;
}
#[rustfmt::skip]
Expand All @@ -231,21 +228,18 @@ pub trait EvalContextExt<'tcx>: crate::MiriInterpCxExt<'tcx> {
=> {
let [f] = check_arg_count(args)?;
let f = this.read_scalar(f)?.to_f64()?;
// Using host floats (but it's fine, these operations do not have guaranteed precision).
let f_host = f.to_host();
let res = match intrinsic_name {
"sinf64" => f_host.sin(),
"cosf64" => f_host.cos(),
"sqrtf64" => f_host.sqrt(), // FIXME Using host floats, this should use full-precision soft-floats
"expf64" => f_host.exp(),
"exp2f64" => f_host.exp2(),
"logf64" => f_host.ln(),
"log10f64" => f_host.log10(),
"log2f64" => f_host.log2(),
let op = match intrinsic_name {
"sinf64" => math::UnaryOp::Sin,
"cosf64" => math::UnaryOp::Cos,
"sqrtf64" => math::UnaryOp::Sqrt,
"expf64" => math::UnaryOp::Exp,
"exp2f64" => math::UnaryOp::Exp2,
"logf64" => math::UnaryOp::Ln,
"log10f64" => math::UnaryOp::Log10,
"log2f64" => math::UnaryOp::Log2,
_ => bug!(),
};
let res = res.to_soft();
let res = this.adjust_nan(res, &[f]);
let res = math::unary_op(this, op, f);
this.write_scalar(res, dest)?;
}

Expand Down Expand Up @@ -299,37 +293,29 @@ pub trait EvalContextExt<'tcx>: crate::MiriInterpCxExt<'tcx> {
let [f1, f2] = check_arg_count(args)?;
let f1 = this.read_scalar(f1)?.to_f32()?;
let f2 = this.read_scalar(f2)?.to_f32()?;
// Using host floats (but it's fine, this operation does not have guaranteed precision).
let res = f1.to_host().powf(f2.to_host()).to_soft();
let res = this.adjust_nan(res, &[f1, f2]);
let res = math::binary_op(this, math::BinaryOp::Powf, f1, f2);
this.write_scalar(res, dest)?;
}
"powf64" => {
let [f1, f2] = check_arg_count(args)?;
let f1 = this.read_scalar(f1)?.to_f64()?;
let f2 = this.read_scalar(f2)?.to_f64()?;
// Using host floats (but it's fine, this operation does not have guaranteed precision).
let res = f1.to_host().powf(f2.to_host()).to_soft();
let res = this.adjust_nan(res, &[f1, f2]);
let res = math::binary_op(this, math::BinaryOp::Powf, f1, f2);
this.write_scalar(res, dest)?;
}

"powif32" => {
let [f, i] = check_arg_count(args)?;
let f = this.read_scalar(f)?.to_f32()?;
let i = this.read_scalar(i)?.to_i32()?;
// Using host floats (but it's fine, this operation does not have guaranteed precision).
let res = f.to_host().powi(i).to_soft();
let res = this.adjust_nan(res, &[f]);
let res = math::powi(this, f, i);
this.write_scalar(res, dest)?;
}
"powif64" => {
let [f, i] = check_arg_count(args)?;
let f = this.read_scalar(f)?.to_f64()?;
let i = this.read_scalar(i)?.to_i32()?;
// Using host floats (but it's fine, this operation does not have guaranteed precision).
let res = f.to_host().powi(i).to_soft();
let res = this.adjust_nan(res, &[f]);
let res = math::powi(this, f, i);
this.write_scalar(res, dest)?;
}

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47 changes: 14 additions & 33 deletions src/intrinsics/simd.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -56,12 +56,12 @@ pub trait EvalContextExt<'tcx>: crate::MiriInterpCxExt<'tcx> {
assert_eq!(dest_len, op_len);

#[derive(Copy, Clone)]
enum Op<'a> {
enum Op {
MirOp(mir::UnOp),
Abs,
Round(rustc_apfloat::Round),
Numeric(Symbol),
HostOp(&'a str),
Math(math::UnaryOp),
}
let which = match intrinsic_name {
"neg" => Op::MirOp(mir::UnOp::Neg),
Expand All @@ -75,7 +75,15 @@ pub trait EvalContextExt<'tcx>: crate::MiriInterpCxExt<'tcx> {
"cttz" => Op::Numeric(sym::cttz),
"bswap" => Op::Numeric(sym::bswap),
"bitreverse" => Op::Numeric(sym::bitreverse),
_ => Op::HostOp(intrinsic_name),
"fsqrt" => Op::Math(math::UnaryOp::Sqrt),
"fsin" => Op::Math(math::UnaryOp::Sin),
"fcos" => Op::Math(math::UnaryOp::Cos),
"fexp" => Op::Math(math::UnaryOp::Exp),
"fexp2" => Op::Math(math::UnaryOp::Exp2),
"flog" => Op::Math(math::UnaryOp::Ln),
"flog2" => Op::Math(math::UnaryOp::Log2),
"flog10" => Op::Math(math::UnaryOp::Log10),
_ => bug!(),
};

for i in 0..dest_len {
Expand All @@ -100,47 +108,20 @@ pub trait EvalContextExt<'tcx>: crate::MiriInterpCxExt<'tcx> {
FloatTy::F128 => unimplemented!("f16_f128"),
}
}
Op::HostOp(host_op) => {
Op::Math(math_op) => {
let ty::Float(float_ty) = op.layout.ty.kind() else {
span_bug!(this.cur_span(), "{} operand is not a float", intrinsic_name)
};
// Using host floats (but it's fine, these operations do not have guaranteed precision).
match float_ty {
FloatTy::F16 => unimplemented!("f16_f128"),
FloatTy::F32 => {
let f = op.to_scalar().to_f32()?;
let f_host = f.to_host();
let res = match host_op {
"fsqrt" => f_host.sqrt(), // FIXME Using host floats, this should use full-precision soft-floats
"fsin" => f_host.sin(),
"fcos" => f_host.cos(),
"fexp" => f_host.exp(),
"fexp2" => f_host.exp2(),
"flog" => f_host.ln(),
"flog2" => f_host.log2(),
"flog10" => f_host.log10(),
_ => bug!(),
};
let res = res.to_soft();
let res = this.adjust_nan(res, &[f]);
let res = math::unary_op(this, math_op, f);
Scalar::from(res)
}
FloatTy::F64 => {
let f = op.to_scalar().to_f64()?;
let f_host = f.to_host();
let res = match host_op {
"fsqrt" => f_host.sqrt(),
"fsin" => f_host.sin(),
"fcos" => f_host.cos(),
"fexp" => f_host.exp(),
"fexp2" => f_host.exp2(),
"flog" => f_host.ln(),
"flog2" => f_host.log2(),
"flog10" => f_host.log10(),
_ => bug!(),
};
let res = res.to_soft();
let res = this.adjust_nan(res, &[f]);
let res = math::unary_op(this, math_op, f);
Scalar::from(res)
}
FloatTy::F128 => unimplemented!("f16_f128"),
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1 change: 1 addition & 0 deletions src/lib.rs
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Expand Up @@ -85,6 +85,7 @@ mod eval;
mod helpers;
mod intrinsics;
mod machine;
mod math;
mod mono_hash_map;
mod operator;
mod provenance_gc;
Expand Down
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