[RTL MVU] Setting lo width max explicitly and updating tests

eki-project · May 28, 2024 · b36c5b1 · b36c5b1
1 parent b0852c8
commit b36c5b1
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Showing 2 changed files with 10 additions and 5 deletions.
diff --git a/finn-rtllib/mvu/mvu_4sx4u.sv b/finn-rtllib/mvu/mvu_4sx4u.sv
@@ -106,7 +106,7 @@ module mvu_4sx4u #(
 	function int unsigned hi_width(input int unsigned  i);
 		return  1 + $clog2(2**(ACCU_WIDTH-lo_width(i)-1)+SIMD);
 	endfunction : hi_width
-	localparam int unsigned  LO_WIDTH_MAX = lo_width(0);
+	localparam int unsigned  LO_WIDTH_MAX = OFFSETS[1] - OFFSETS[0];
 	localparam int unsigned  HI_WIDTH_MAX = hi_width(2);
 
 	localparam int unsigned  A_WIDTH = 23 + 2*VERSION;	// Width of A datapath

diff --git a/tests/fpgadataflow/test_fpgadataflow_mvau.py b/tests/fpgadataflow/test_fpgadataflow_mvau.py
@@ -635,17 +635,19 @@ def test_mvau_fifocharacterize_rtlsim(
 
 @pytest.mark.parametrize("mh", [18])
 @pytest.mark.parametrize("mw", [128])
-@pytest.mark.parametrize("pe", [1, 6, 9, 18])
-@pytest.mark.parametrize("simd", [1, 4, 16, 64, 128])
+@pytest.mark.parametrize("pe", [1, 9, 18])
+@pytest.mark.parametrize("simd", [1, 64, 128])
 @pytest.mark.parametrize("idt", [DataType["UINT4"], DataType["UINT8"]])
 @pytest.mark.parametrize("wdt", [DataType["INT4"], DataType["INT8"]])
-@pytest.mark.parametrize("part", ["xcvc1902-vsva2197-2MP-e-S", "xcku3p-ffva676-1-e"])
+@pytest.mark.parametrize(
+    "part", ["xcvc1902-vsva2197-2MP-e-S", "xcku3p-ffva676-1-e", "xc7z020clg400-1"]
+)
 @pytest.mark.parametrize("clk_ns", [1.66, 4])
 @pytest.mark.fpgadataflow
 @pytest.mark.slow
 @pytest.mark.vivado
 def test_fpgadataflow_rtl_mvau(mh, mw, pe, simd, idt, wdt, part, clk_ns):
-    if part == "xcku3p-ffva676-1-e" and clk_ns != 1.66:
+    if part != "xcvc1902-vsva2197-2MP-e-S" and clk_ns != 1.66:
         pytest.skip(
             """Skip test for varying clk for devices other than Versal,
             since this variable only affects DSP58s"""
@@ -657,6 +659,9 @@ def test_fpgadataflow_rtl_mvau(mh, mw, pe, simd, idt, wdt, part, clk_ns):
     ifm = helper.make_tensor_value_info("ifm", TensorProto.FLOAT, [1, ofm_h, ofm_w, mw])
     ofm = helper.make_tensor_value_info("ofm", TensorProto.FLOAT, (1, ofm_h, ofm_w, mh))
     W = gen_finn_dt_tensor(wdt, (mw, mh))
+    # if 7 series, force weights to narrow range
+    if part == "xc7z020clg400-1":
+        W = np.clip(W, wdt.min() + 1, wdt.max())
     model = make_single_matmul_modelwrapper(ifm, ofm, idt, wdt, W)
     model = model.transform(GiveUniqueNodeNames())
     model = model.transform(GiveReadableTensorNames())