feat: use fp8 multiply for blackwell bwgmma

src/main/scala/radiance/core/TensorCoreBlackwell.scala

@@ -6,6 +6,29 @@ package radiance.core
 import chisel3._
 import chisel3.util._
 
+object TensorCoreBlackwellFP8Packing {
+  def fp8Byte(x: UInt, idx: Int): UInt = {
+    x((idx + 1) * 8 - 1, idx * 8)
+  }
+
+  def selectA(operandA: UInt, k: Int, elemM: UInt, numLanes: Int): UInt = {
+    if (numLanes == 4) {
+      Mux(elemM.asBool, fp8Byte(operandA, 8 + k), fp8Byte(operandA, k))
+    } else {
+      MuxLookup(elemM, fp8Byte(operandA, k))(Seq(
+        0.U -> fp8Byte(operandA, k),
+        1.U -> fp8Byte(operandA, 8 + k),
+        2.U -> fp8Byte(operandA, 16 + k),
+        3.U -> fp8Byte(operandA, 24 + k)
+      ))
+    }
+  }
+
+  def selectB(operandB: UInt, k: Int, elemN: UInt): UInt = {
+    Mux(elemN.asBool, fp8Byte(operandB, 8 + k), fp8Byte(operandB, k))
+  }
+}
+
 class TensorCoreBlackwell(
     val numWarps: Int,
     val numLanes: Int,
@@ -13,7 +36,7 @@ class TensorCoreBlackwell(
     val numSourceIds: Int = 16,
     val numFPRegs: Int = 32
 ) extends Module {
-  require(half, "Blackwell MMA currently supports FP16 inputs only")
+  require(half, "Blackwell MMA compatibility flag must remain true; BWGMMA inputs are FP8 E4M3 on this branch")
   require(numLanes == 4 || numLanes == 8,
     s"Blackwell MMA currently supports 4 or 8 lanes, got ${numLanes}")
 
@@ -198,30 +221,16 @@ class TensorCoreBlackwell(
   val dpuInValid = WireDefault(false.B)
   val dpu = Module(new TensorDotProductUnit(
     dim = 8,
-    half = true
+    half = false,
+    inputType = TensorInputType.FP8E4M3
   ))
 
-  private def halfWord(x: UInt, idx: Int): UInt = {
-    x((idx + 1) * 16 - 1, idx * 16)
-  }
-
   val elemM = if (numLanes == 4) elemReg(0, 0) else elemReg(1, 0)
   val elemN = if (numLanes == 4) elemReg(1) else elemReg(2)
   dpu.io.in.valid := dpuInValid
   for (k <- 0 until 8) {
-    dpu.io.in.bits.a(k) := (
-      if (numLanes == 4) {
-        Mux(elemM.asBool, halfWord(operandA, 8 + k), halfWord(operandA, k))
-      } else {
-        MuxLookup(elemM, halfWord(operandA, k))(Seq(
-          0.U -> halfWord(operandA, k),
-          1.U -> halfWord(operandA, 8 + k),
-          2.U -> halfWord(operandA, 16 + k),
-          3.U -> halfWord(operandA, 24 + k)
-        ))
-      }
-    )
-    dpu.io.in.bits.b(k) := Mux(elemN.asBool, halfWord(operandB, 8 + k), halfWord(operandB, k))
+    dpu.io.in.bits.a(k) := TensorCoreBlackwellFP8Packing.selectA(operandA, k, elemM, numLanes)
+    dpu.io.in.bits.b(k) := TensorCoreBlackwellFP8Packing.selectB(operandB, k, elemN)
   }
   dpu.io.in.bits.c := cWords(elemReg)
   dpu.io.stall := false.B

src/main/scala/radiance/core/TensorDPU.scala

@@ -7,17 +7,116 @@ import chisel3._
 import chisel3.util._
 import freechips.rocketchip.tile
 
+object FP8E4M3 {
+  private val Bias = 7
+
+  private def decodeToFloat(bits: Int): Float = {
+    val sign = (bits >> 7) & 0x1
+    val exp = (bits >> 3) & 0xf
+    val frac = bits & 0x7
+
+    val magnitude =
+      if (exp == 0) {
+        if (frac == 0) 0.0
+        else (frac.toDouble / 8.0) * Math.pow(2.0, 1 - Bias)
+      } else {
+        (1.0 + frac.toDouble / 8.0) * Math.pow(2.0, exp - Bias)
+      }
+
+    val value = if (sign == 1) -magnitude else magnitude
+    value.toFloat
+  }
+
+  private def fp32Bits(bits: Int): BigInt = {
+    BigInt(java.lang.Float.floatToRawIntBits(decodeToFloat(bits)).toLong & 0xffffffffL)
+  }
+
+  def toFloat32(x: UInt): UInt = {
+    MuxLookup(x, 0.U(32.W))((0 until 256).map { bits =>
+      bits.U(8.W) -> fp32Bits(bits).U(32.W)
+    })
+  }
+}
+
+object FP8E4M3MulToFloat32 {
+  private val Bias = 7
+
+  def apply(a: UInt, b: UInt): UInt = {
+    val sign = a(7) ^ b(7)
+    val expA = a(6, 3)
+    val expB = b(6, 3)
+    val fracA = a(2, 0)
+    val fracB = b(2, 0)
+    val zeroA = expA === 0.U && fracA === 0.U
+    val zeroB = expB === 0.U && fracB === 0.U
+    val isZero = zeroA || zeroB
+
+    val sigA = Mux(expA === 0.U, Cat(0.U(1.W), fracA), Cat(1.U(1.W), fracA))
+    val sigB = Mux(expB === 0.U, Cat(0.U(1.W), fracB), Cat(1.U(1.W), fracB))
+    val prodSig = sigA * sigB
+
+    val scaleA = Wire(SInt(6.W))
+    val scaleB = Wire(SInt(6.W))
+    scaleA := Mux(expA === 0.U, -9.S(6.W), expA.zext - (Bias + 3).S(6.W))
+    scaleB := Mux(expB === 0.U, -9.S(6.W), expB.zext - (Bias + 3).S(6.W))
+
+    val msb = Wire(UInt(3.W))
+    when(prodSig(7)) {
+      msb := 7.U
+    }.elsewhen(prodSig(6)) {
+      msb := 6.U
+    }.elsewhen(prodSig(5)) {
+      msb := 5.U
+    }.elsewhen(prodSig(4)) {
+      msb := 4.U
+    }.elsewhen(prodSig(3)) {
+      msb := 3.U
+    }.elsewhen(prodSig(2)) {
+      msb := 2.U
+    }.elsewhen(prodSig(1)) {
+      msb := 1.U
+    }.otherwise {
+      msb := 0.U
+    }
+
+    val normalized = (prodSig << (7.U - msb))(7, 0)
+    val exponent = (scaleA + scaleB + msb.zext + 127.S(10.W)).asUInt(7, 0)
+    val fraction = Cat(normalized(6, 0), 0.U(16.W))
+    Mux(isZero, Cat(sign, 0.U(31.W)), Cat(sign, exponent, fraction))
+  }
+}
+
+object TensorInputType extends Enumeration {
+  val FP16, FP32, FP8E4M3 = Value
+
+  def fromHalf(half: Boolean): Value = {
+    if (half) FP16 else FP32
+  }
+}
+
 // Implements the four-element dot product (FEDP) unit in Volta Tensor Cores.
 // `half`: if True, generate fp16 MACs; if False fp32.
 class TensorDotProductUnit(
-  val dim: Int = 4,
-  val half: Boolean
+  val dim: Int,
+  val half: Boolean,
+  val inputType: TensorInputType.Value
 ) extends Module with tile.HasFPUParameters {
-  val tIn = if (half) tile.FType.H else tile.FType.S
+  def this(dim: Int = 4, half: Boolean) = {
+    this(dim, half, TensorInputType.fromHalf(half))
+  }
+
+  val tIn = inputType match {
+    case TensorInputType.FP16 => tile.FType.H
+    case TensorInputType.FP32 => tile.FType.S
+    case TensorInputType.FP8E4M3 => tile.FType.S
+  }
   // output datatype fixed to single-precision
   val tOut = tile.FType.S
 
-  val inFLen = tIn.ieeeWidth
+  val inFLen = inputType match {
+    case TensorInputType.FP8E4M3 => 8
+    case _ => tIn.ieeeWidth
+  }
   val outFLen = tOut.ieeeWidth
   val fLen = outFLen // needed for HasFPUParameters
   val minFLen = 16 // fp16
@@ -40,20 +139,39 @@ class TensorDotProductUnit(
   // [IEEE] -> recode() -> unbox() -> [Hardfloat] -> box() -> ieee() -> [IEEE]
   // make sure recoding/uncoding happens only at the edge, not at every
   // pipeline stage inside the dpu
-  val tag = if (half) H else S
-  val in1 = io.in.bits.a.map(x => unbox(recode(x, tag), tag, Some(tIn)))
-  val in2 = io.in.bits.b.map(x => unbox(recode(x, tag), tag, Some(tIn)))
-  val in3 = unbox(recode(io.in.bits.c, S), S, Some(tOut))
+  val tag = inputType match {
+    case TensorInputType.FP16 => H
+    case TensorInputType.FP32 => S
+    case TensorInputType.FP8E4M3 => S
+  }
+  if (inputType == TensorInputType.FP8E4M3) {
+    val dpu = Module(new DotProductPipeFP8E4M3(dim))
+    dpu.io.in.valid := io.in.valid
+    dpu.io.in.bits.a := io.in.bits.a
+    dpu.io.in.bits.b := io.in.bits.b
+    dpu.io.in.bits.c := io.in.bits.c
+    dpu.io.stall := io.stall
 
-  val dpu = Module(new DotProductPipe(dim, tIn, tOut))
-  dpu.io.in.valid := io.in.valid
-  dpu.io.in.bits.a := in1
-  dpu.io.in.bits.b := in2
-  dpu.io.in.bits.c := in3
-  dpu.io.stall := io.stall
+    io.out.valid := dpu.io.out.valid
+    io.out.bits.data := dpu.io.out.bits.data
+  } else {
+    def recodeInput(x: Bits): UInt = {
+      unbox(recode(x.asUInt, tag), tag, Some(tIn))
+    }
+    val in1 = io.in.bits.a.map(recodeInput)
+    val in2 = io.in.bits.b.map(recodeInput)
+    val in3 = unbox(recode(io.in.bits.c, S), S, Some(tOut))
 
-  io.out.valid := dpu.io.out.valid
-  io.out.bits.data := ieee(box(dpu.io.out.bits.data, S))
+    val dpu = Module(new DotProductPipe(dim, tIn, tOut))
+    dpu.io.in.valid := io.in.valid
+    dpu.io.in.bits.a := in1
+    dpu.io.in.bits.b := in2
+    dpu.io.in.bits.c := in3
+    dpu.io.stall := io.stall
+
+    io.out.valid := dpu.io.out.valid
+    io.out.bits.data := ieee(box(dpu.io.out.bits.data, S))
+  }
 }
 
 // An implementation of chisel3.util.Pipe that supports stalls.
@@ -236,6 +354,89 @@ class DotProductPipe(dim: Int, inputType: tile.FType, outputType: tile.FType) ex
   io.out.bits.data := accStageOut.bits
 }
 
+class DotProductPipeFP8E4M3(dim: Int) extends Module with tile.HasFPUParameters {
+  val tOut = tile.FType.S
+  val outExpWidth = tOut.exp
+  val outSigWidth = tOut.sig
+  val recOutFLen = outExpWidth + outSigWidth + 1
+  val fLen = tOut.ieeeWidth
+  val minFLen = 16
+  def xLen = 32
+
+  val io = IO(new Bundle {
+    val in = Flipped(Valid(new Bundle {
+      val a = Vec(dim, Bits(8.W))
+      val b = Vec(dim, Bits(8.W))
+      val c = Bits(32.W)
+    }))
+    val stall = Input(Bool())
+    val out = Valid(new Bundle {
+      val data = Bits(32.W)
+    })
+  })
+
+  val productRecoded = io.in.bits.a.zip(io.in.bits.b).map { case (a, b) =>
+    unbox(recode(FP8E4M3MulToFloat32(a.asUInt, b.asUInt), S), S, Some(tOut))
+  }
+  val inC = unbox(recode(io.in.bits.c, S), S, Some(tOut))
+
+  val productStageOut = StallingPipe(io.stall, io.in.valid, VecInit(productRecoded))
+  val productStageC = StallingPipe(io.stall, io.in.valid, inC)
+
+  val log2Dim = log2Ceil(dim)
+  require(dim == (1 << log2Dim), s"dim (${dim}) is not power of two!")
+
+  val interim = (log2Dim to 0 by -1).map { i =>
+    Wire(Valid(Vec(1 << i, Bits(recOutFLen.W))))
+  }
+  val interimC = (log2Dim to 0 by -1).map(_ => Wire(Valid(Bits(recOutFLen.W))))
+  interim(0) := productStageOut
+  interimC(0) := productStageC
+
+  val (addStageOut, addStageC) = (interim zip interimC).reduce {
+    (inputsAndC, outputsAndC) => {
+      val (inputs, inC) = inputsAndC
+      val (outputs, outC) = outputsAndC
+
+      require(inputs.bits.length == 2 * outputs.bits.length)
+      val thisDim = inputs.bits.length
+      val adders = Seq.fill(thisDim / 2)(
+        Module(new hardfloat.AddRecFN(outExpWidth, outSigWidth))
+      )
+      val addOuts = adders.zipWithIndex.map { case (a, i) =>
+        a.io.subOp := 0.U
+        a.io.a := inputs.bits(2 * i + 0)
+        a.io.b := inputs.bits(2 * i + 1)
+        a.io.roundingMode := hardfloat.consts.round_near_even
+        a.io.detectTininess := hardfloat.consts.tininess_afterRounding
+        a.io.out
+      }
+
+      outputs := StallingPipe(io.stall, inputs.valid, VecInit(addOuts))
+      outC := StallingPipe(io.stall, inputs.valid, inC.bits)
+      when(inputs.valid =/= inC.valid) {
+        printf("WARN: DotProductPipeFP8E4M3 input/C valid mismatch: inputs=%d c=%d\n",
+          inputs.valid, inC.valid)
+      }
+
+      (outputs, outC)
+    }
+  }
+  require(addStageOut.bits.length == 1)
+
+  val acc = Module(new hardfloat.AddRecFN(outExpWidth, outSigWidth))
+  acc.io.subOp := 0.U
+  acc.io.a := addStageOut.bits(0)
+  acc.io.b := addStageC.bits
+  acc.io.roundingMode := hardfloat.consts.round_near_even
+  acc.io.detectTininess := hardfloat.consts.tininess_afterRounding
+
+  val accStageOut = StallingPipe(io.stall, addStageOut.valid, acc.io.out)
+
+  io.out.valid := accStageOut.valid
+  io.out.bits.data := ieee(box(accStageOut.bits, S))
+}
+
 class MulAddRecFNPipe(latency: Int, expWidth: Int, sigWidth: Int) extends Module {
   require(latency <= 2)
 

src/test/scala/radiance/FP8E4M3Test.scala

@@ -0,0 +1,110 @@
+package radiance.core
+
+import chisel3._
+import chiseltest._
+import org.scalatest.flatspec.AnyFlatSpec
+
+class FP8E4M3DecodeHarness extends Module {
+  val io = IO(new Bundle {
+    val in = Input(UInt(8.W))
+    val out = Output(UInt(32.W))
+  })
+
+  io.out := FP8E4M3.toFloat32(io.in)
+}
+
+class FP8E4M3MulHarness extends Module {
+  val io = IO(new Bundle {
+    val a = Input(UInt(8.W))
+    val b = Input(UInt(8.W))
+    val out = Output(UInt(32.W))
+  })
+
+  io.out := FP8E4M3MulToFloat32(io.a, io.b)
+}
+
+class FP8E4M3Test extends AnyFlatSpec with ChiselScalatestTester {
+  behavior of "FP8E4M3"
+
+  it should "decode representative E4M3 values to FP32 bits" in {
+    test(new FP8E4M3DecodeHarness) { c =>
+      Seq(
+        0x00 -> 0x00000000L,
+        0x80 -> 0x80000000L,
+        0x38 -> 0x3f800000L,
+        0x40 -> 0x40000000L,
+        0x30 -> 0x3f000000L,
+        0x3c -> 0x3fc00000L
+      ).foreach { case (fp8, fp32) =>
+        c.io.in.poke(fp8.U)
+        c.clock.step()
+        c.io.out.expect(fp32.U)
+      }
+    }
+  }
+
+  it should "multiply E4M3 operands with FP8-width significands and return FP32 bits" in {
+    test(new FP8E4M3MulHarness) { c =>
+      Seq(
+        (0x38, 0x40, 0x40000000L), // 1.0 * 2.0 = 2.0
+        (0x30, 0x3c, 0x3f400000L), // 0.5 * 1.5 = 0.75
+        (0xb8, 0x40, 0xc0000000L), // -1.0 * 2.0 = -2.0
+        (0x00, 0x40, 0x00000000L), // 0.0 * 2.0 = 0.0
+        (0x80, 0x40, 0x80000000L)  // -0.0 * 2.0 = -0.0
+      ).foreach { case (a, b, out) =>
+        c.io.a.poke(a.U)
+        c.io.b.poke(b.U)
+        c.clock.step()
+        c.io.out.expect(out.U)
+      }
+    }
+  }
+
+  it should "run an 8-wide FP8 dot product with FP32 accumulation" in {
+    test(new TensorDotProductUnit(8, half = false, inputType = TensorInputType.FP8E4M3)) { c =>
+      c.io.in.valid.poke(true.B)
+      c.io.stall.poke(false.B)
+      for (i <- 0 until 8) {
+        c.io.in.bits.a(i).poke(0x38.U(8.W))
+        c.io.in.bits.b(i).poke(0x40.U(8.W))
+      }
+      c.io.in.bits.c.poke(0x3f800000L.U(32.W))
+
+      c.io.out.valid.expect(false.B)
+      c.clock.step()
+      c.io.in.valid.poke(false.B)
+      c.io.out.valid.expect(false.B)
+
+      c.clock.step()
+      c.clock.step()
+      c.clock.step()
+      c.clock.step()
+      c.io.out.valid.expect(true.B)
+      c.io.out.bits.data.expect(0x41880000L.U)
+    }
+  }
+
+  it should "run an 8-wide fractional FP8 dot product with FP32 accumulation" in {
+    test(new TensorDotProductUnit(8, half = false, inputType = TensorInputType.FP8E4M3)) { c =>
+      c.io.in.valid.poke(true.B)
+      c.io.stall.poke(false.B)
+      for (i <- 0 until 8) {
+        c.io.in.bits.a(i).poke(0x30.U(8.W))
+        c.io.in.bits.b(i).poke(0x3c.U(8.W))
+      }
+      c.io.in.bits.c.poke(0x40000000L.U(32.W))
+
+      c.io.out.valid.expect(false.B)
+      c.clock.step()
+      c.io.in.valid.poke(false.B)
+      c.io.out.valid.expect(false.B)
+
+      c.clock.step()
+      c.clock.step()
+      c.clock.step()
+      c.clock.step()
+      c.io.out.valid.expect(true.B)
+      c.io.out.bits.data.expect(0x41000000L.U)
+    }
+  }
+}

src/test/scala/radiance/TensorCoreBlackwellExtendedTest.scala

@@ -68,22 +68,22 @@ class TensorCoreBlackwellExtendedTest extends AnyFlatSpec with ChiselScalatestTe
       val cBase = BigInt(0x600)  // row 48, C tile rows 48~79 (no overlap with A)
       val bBase = BigInt(0x800)
 
-      val fp16One = BigInt(0x3c00)
+      val fp8One = BigInt(0x38)
       val fp32Zero = BigInt(0)
       // 4 sets × 8 dot products × (1.0 × 2.0) = 64.0f
       val fp32SixtyFour = BigInt(0x42800000L)
 
       // Populate TMEM A at offset aBase (all 32 frags)
-      val aFrag = packWords(Seq.fill(16)(fp16One), 16)
+      val aFrag = packWords(Seq.fill(32)(fp8One), 8)
       val cFrag = packWords(Seq.fill(numLanes)(fp32Zero), 32)
       for (i <- 0 until 32) {
         tmem(aBase / fragBytes + i) = aFrag
         tmem(cBase / fragBytes + i) = cFrag
       }
 
-      // SMEM B with fp16 2.0
-      val fp16Two = BigInt(0x4000)
-      val bFrag = packWords(Seq.fill(16)(fp16Two), 16)
+      // SMEM B with packed FP8 E4M3 2.0
+      val fp8Two = BigInt(0x40)
+      val bFrag = packWords(Seq.fill(32)(fp8Two), 8)
       val bMem = mutable.Map[BigInt, BigInt]().withDefaultValue(bFrag)
       for (i <- 0 until 32) bMem(bBase + i * fragBytes) = bFrag
 

src/test/scala/radiance/TensorCoreBlackwellFP8Test.scala

@@ -0,0 +1,76 @@
+package radiance.core
+
+import chisel3._
+import chiseltest._
+import org.scalatest.flatspec.AnyFlatSpec
+
+class TensorCoreBlackwellFP8MicrostepHarness extends Module {
+  val io = IO(new Bundle {
+    val valid = Input(Bool())
+    val operandA = Input(UInt(512.W))
+    val operandB = Input(UInt(256.W))
+    val c = Input(UInt(32.W))
+    val elemM = Input(UInt(2.W))
+    val elemN = Input(UInt(1.W))
+    val outValid = Output(Bool())
+    val out = Output(UInt(32.W))
+  })
+
+  val dpu = Module(new TensorDotProductUnit(
+    dim = 8,
+    half = false,
+    inputType = TensorInputType.FP8E4M3
+  ))
+
+  dpu.io.in.valid := io.valid
+  for (k <- 0 until 8) {
+    dpu.io.in.bits.a(k) := TensorCoreBlackwellFP8Packing.selectA(io.operandA, k, io.elemM, numLanes = 8)
+    dpu.io.in.bits.b(k) := TensorCoreBlackwellFP8Packing.selectB(io.operandB, k, io.elemN)
+  }
+  dpu.io.in.bits.c := io.c
+  dpu.io.stall := false.B
+
+  io.outValid := dpu.io.out.valid
+  io.out := dpu.io.out.bits.data
+}
+
+class TensorCoreBlackwellFP8Test extends AnyFlatSpec with ChiselScalatestTester {
+  behavior of "TensorCoreBlackwell FP8 operand microstep"
+
+  private def packWords(words: Seq[BigInt], width: Int): BigInt = {
+    val mask = (BigInt(1) << width) - 1
+    words.zipWithIndex.foldLeft(BigInt(0)) {
+      case (acc, (word, i)) => acc | ((word & mask) << (i * width))
+    }
+  }
+
+  it should "select packed FP8 E4M3 operands and accumulate into FP32" in {
+    test(new TensorCoreBlackwellFP8MicrostepHarness) { c =>
+      val fp8One = BigInt(0x38)
+      val fp8Two = BigInt(0x40)
+      val fp32One = BigInt(0x3f800000L)
+      val fp32Seventeen = BigInt(0x41880000L)
+      val operandA = packWords(Seq.fill(64)(fp8One), 8)
+      val operandB = packWords(Seq.fill(32)(fp8Two), 8)
+
+      c.io.valid.poke(true.B)
+      c.io.operandA.poke(operandA.U)
+      c.io.operandB.poke(operandB.U)
+      c.io.c.poke(fp32One.U)
+      c.io.elemM.poke(0.U)
+      c.io.elemN.poke(0.U)
+      c.io.outValid.expect(false.B)
+
+      c.clock.step()
+      c.io.valid.poke(false.B)
+      c.io.outValid.expect(false.B)
+
+      c.clock.step()
+      c.clock.step()
+      c.clock.step()
+      c.clock.step()
+      c.io.outValid.expect(true.B)
+      c.io.out.expect(fp32Seventeen.U)
+    }
+  }
+}

src/test/scala/radiance/TensorCoreBlackwellTest.scala

@@ -249,13 +249,13 @@ class TensorCoreBlackwellTest extends AnyFlatSpec with ChiselScalatestTester {
       val bBase = BigInt(0x800)
       val cBase = BigInt(0x1000)
 
-      // A: all fp16 1.0 (0x3c00), 16 halves per frag
-      val fp16One = BigInt(0x3c00)
-      val fp16Two = BigInt(0x4000)
+      // A/B: packed FP8 E4M3 bytes, 32 elements per 256-bit frag
+      val fp8One = BigInt(0x38)
+      val fp8Two = BigInt(0x40)
       val fp32One = BigInt(0x3f800000)
       val fp32SixtyFive = BigInt(0x42820000)
-      val aFrag = packWords(Seq.fill(16)(fp16One), 16)
-      val bFrag = packWords(Seq.fill(16)(fp16Two), 16)
+      val aFrag = packWords(Seq.fill(32)(fp8One), 8)
+      val bFrag = packWords(Seq.fill(32)(fp8Two), 8)
       val cFrag = packWords(Seq.fill(numLanes)(fp32One), 32)
       val expectedCFrag = packWords(Seq.fill(numLanes)(fp32SixtyFive), 32)