Documentation, cleanup, multi-valued logic

docs/datastructures.rst

@@ -20,15 +20,10 @@ Circuit Graph - :mod:`kyupy.circuit`
 .. autoclass:: kyupy.circuit.Circuit
    :members:
 
-M-Valued Logic - :mod:`kyupy.logic`
------------------------------------
+Multi-Valued Logic - :mod:`kyupy.logic`
+---------------------------------------
 
 .. automodule:: kyupy.logic
    :members:
 
-.. autoclass:: kyupy.logic.MVArray
-   :members:
-
-.. autoclass:: kyupy.logic.BPArray
-   :members:
 

docs/parsers.rst

@@ -1,12 +1,42 @@
 Parsers
 =======
 
-bench
+KyuPy contains simple (and often incomplete) parsers for common file formats.
+These parsers are tailored to the most common use-cases to keep the grammars and the code-base as simple as possible.
 
-verilog
+Each of the modules export a function ``parse()`` for parsing a string directly and a function
+``load()`` for loading a file. Files with a '.gz' extension are uncompressed on-the-fly.
 
-SDF
 
-STIL
+Verilog - :mod:`kyupy.verilog`
+------------------------------
 
+.. automodule:: kyupy.verilog
+   :members: parse, load
 
+
+Bench Format - :mod:`kyupy.bench`
+---------------------------------
+
+.. automodule:: kyupy.bench
+   :members: parse, load
+
+
+Standard Test Interface Language - :mod:`kyupy.stil`
+----------------------------------------------------
+
+.. automodule:: kyupy.stil
+   :members: parse, load
+
+.. autoclass:: kyupy.stil.StilFile
+   :members:
+
+
+Standard Delay Format - :mod:`kyupy.sdf`
+----------------------------------------
+
+.. automodule:: kyupy.sdf
+   :members: parse, load
+
+.. autoclass:: kyupy.sdf.DelayFile
+   :members:

docs/simulators.rst

@@ -1,8 +1,20 @@
 Simulators
 ==========
 
-Logic Sim
+Logic Simulation - :mod:`kyupy.logic_sim`
+-----------------------------------------
 
-Wave Sim
+.. autoclass:: kyupy.logic_sim.LogicSim
+   :members:
 
 
+Timing Simulation - :mod:`kyupy.wave_sim`
+-----------------------------------------
+
+.. automodule:: kyupy.wave_sim
+
+.. autoclass:: kyupy.wave_sim.WaveSim
+   :members:
+
+.. autoclass:: kyupy.wave_sim.WaveSimCuda
+   :members:

src/kyupy/__init__.py

@@ -1,10 +1,13 @@
-"""This package provides tools for high-performance processing and validation
-of non-hierarchical VLSI circuits to aid rapid prototyping of research code
-in the fields of VLSI test, diagnosis and reliability.
+"""A package for processing and analysis of non-hierarchical gate-level VLSI designs.
+
+It contains fundamental building blocks for research software in the fields of VLSI test, diagnosis and reliability.
 """
 
 import time
 import importlib.util
+import gzip
+
+import numpy as np
 
 
 class Log:
@@ -97,12 +100,27 @@ if importlib.util.find_spec('numba') is not None:
         list(numba.cuda.gpus)
         from numba import cuda
     except CudaSupportError:
-        log.warn('Cuda unavailable. Falling back to pure python')
+        log.warn('Cuda unavailable. Falling back to pure Python.')
         cuda = MockCuda()
 else:
     numba = MockNumba()
     cuda = MockCuda()
-    log.warn('Numba unavailable. Falling back to pure python')
+    log.warn('Numba unavailable. Falling back to pure Python.')
+
 
+_pop_count_lut = np.asarray([bin(x).count('1') for x in range(256)])
 
 
+def popcount(a):
+    return np.sum(_pop_count_lut[a])
+
+
+def readtext(file):
+    if hasattr(file, 'read'):
+        return file.read()
+    if str(file).endswith('.gz'):
+        with gzip.open(file, 'rt') as f:
+            return f.read()
+    else:
+        with open(file, 'rt') as f:
+            return f.read()

src/kyupy/bench.py

@@ -1,5 +1,16 @@
+"""A parser for the ISCAS89 benchmark format.
+
+The ISCAS89 benchmark format (`.bench`-suffix) is a very simple textual description of gate-level netlists.
+Historically it was first used in the
+`ISCAS89 benchmark set <https://people.engr.ncsu.edu/brglez/CBL/benchmarks/ISCAS89/>`_.
+Besides loading these benchmarks, this module is also useful for easily constructing simple circuits:
+``c = bench.parse('input(x, y) output(a, o, n) a=and(x,y) o=or(x,y) n=not(x)')``.
+"""
+
 from lark import Lark, Transformer
+
 from .circuit import Circuit, Node, Line
+from . import readtext
 
 
 class BenchTransformer(Transformer):
@@ -21,7 +32,6 @@ class BenchTransformer(Transformer):
         [Line(self.c, d, cell) for d in drivers]
 
 
-def parse(bench):
 grammar = r"""
     start: (statement)*
     statement: input | output | assignment
@@ -32,12 +42,23 @@ def parse(bench):
     NAME: /[-_a-z0-9]+/i
     %ignore ( /\r?\n/ | "#" /[^\n]*/ | /[\t\f ]/ )+
     """
-    name = None
-    if '(' not in str(bench):  # No parentheses?: Assuming it is a file name.
-        name = str(bench).replace('.bench', '')
-        with open(bench, 'r') as f:
-            text = f.read()
-    else:
-        text = bench
+
+
+def parse(text, name=None):
+    """Parses the given ``text`` as ISCAS89 bench code.
+
+    :param text: A string with bench code.
+    :param name: The name of the circuit. Circuit names are not included in bench descriptions.
+    :return: A :class:`Circuit` object.
+    """
     return Lark(grammar, parser="lalr", transformer=BenchTransformer(name)).parse(text)
 
+
+def load(file, name=None):
+    """Parses the contents of ``file`` as ISCAS89 bench code.
+
+    :param file: The file to be loaded.
+    :param name: The name of the circuit. If none given, the file name is used as circuit name.
+    :return: A :class:`Circuit` object.
+    """
+    return parse(readtext(file), name=name or str(file))

src/kyupy/bittools.py

@@ -1,23 +0,0 @@
-import numpy as np
-import importlib.util
-if importlib.util.find_spec('numba') is not None:
-    import numba
-else:
-    from . import numba
-    print('Numba unavailable. Falling back to pure python')
-
-
-_pop_count_lut = np.asarray([bin(x).count('1') for x in range(256)])
-
-
-def popcount(a):
-    return np.sum(_pop_count_lut[a])
-
-
-_bit_in_lut = np.array([2 ** x for x in range(7, -1, -1)], dtype='uint8')
-
-
-@numba.njit
-def bit_in(a, pos):
-    return a[pos >> 3] & _bit_in_lut[pos & 7]
-

src/kyupy/logic.py

@@ -1,30 +1,23 @@
-"""Data structures for 2-valued, 4-valued, and 8-valued logic computation.
+"""This module contains definitions and data structures for 2-, 4-, and 8-valued logic operations.
 
-Integer constants: ZERO, ONE, UNASSIGNED, UNKNOWN, RISING, FALLING, PPULSE, NPULSE.
+8 logic values are defined as integer constants.
 
-* The bits in the constants have the following meaning:
+* For 2-valued logic: ``ZERO`` and ``ONE``
+* 4-valued logic adds: ``UNASSIGNED`` and ``UNKNOWN``
+* 8-valued logic adds: ``RISE``, ``FALL``, ``PPULSE``, and ``NPULSE``.
+
+The bits in these constants have the following meaning:
 
   * bit 0: Final/settled binary value of a signal
   * bit 1: Initial binary value of a signal
-  * bit 2: 1, if activity or transitions are present on a signal
-
-Special meaning is given to values where bits 0 and 1 differ, but activity is 0.
-These values are interpreted as 'unknown' or 'unassigned' in 4-valued and 8-valued logic.
-
-* 4-valued logic: 2 bits for storage, the third bit is implicitly 0
+  * bit 2: Activity or transitions are present on a signal
 
-  * 0 (0b00) : '0', 0, False, logic-0 (kyupy.logic.ZERO)
-  * 1 (0b01) : '-', None, unassigned (kyupy.logic.UNASSIGNED)
-  * 2 (0b10) : 'X', unknown (kyupy.logic.UNKNOWN)
-  * 3 (0b11) : '1', 1, True, logic-1 (kyupy.logic.ONE)
-
-* 8-valued logic: 3 bits for storage, adds the following 4 interpretations
-
-  * 4 (0b100) : 'P', positive pulse 0 -> 1 -> 0 (kyupy.logic.PPULSE)
-  * 5 (0b101) : 'R', rising transition (kyupy.logic.RISING)
-  * 6 (0b110) : 'F', falling transition (kyupy.logic.FALLING)
-  * 7 (0b111) : 'N', negative pulse 1 -> 0 -> 1 (kyupy.logic.NPULSE)
+Special meaning is given to values where bits 0 and 1 differ, but bit 2 (activity) is 0.
+These values are interpreted as ``UNKNOWN`` or ``UNASSIGNED`` in 4-valued and 8-valued logic.
 
+In general, 2-valued logic only considers bit 0, 4-valued logic considers bits 0 and 1, and 8-valued logic
+considers all 3 bits.
+The only exception is constant ``ONE=0b11`` which has two bits set for all logics including 2-valued logic.
 """
 
 import math
@@ -32,16 +25,36 @@ from collections.abc import Iterable
 
 import numpy as np
 
+from . import numba
+
+
 ZERO = 0b000
-"""Integer constant ``0b000`` for logic-0.
+"""Integer constant ``0b000`` for logic-0. ``'0'``, ``0``, ``False``, ``'L'``, and ``'l'`` are interpreted as ``ZERO``.
+"""
+UNKNOWN = 0b001
+"""Integer constant ``0b001`` for unknown or conflict. ``'X'``, or any other value is interpreted as ``UNKNOWN``.
+"""
+UNASSIGNED = 0b010
+"""Integer constant ``0b010`` for unassigned or high-impedance. ``'-'``, ``None``, ``'Z'``, and ``'z'`` are
+interpreted as ``UNASSIGNED``.
 """
-UNASSIGNED = 0b001
-UNKNOWN = 0b010
 ONE = 0b011
+"""Integer constant ``0b011`` for logic-1. ``'1'``, ``1``, ``True``, ``'H'``, and ``'h'`` are interpreted as ``ONE``.
+"""
 PPULSE = 0b100
-RISING = 0b101
-FALLING = 0b110
+"""Integer constant ``0b100`` for positive pulse, meaning initial and final values are 0, but there is some activity
+on a signal. ``'P'``, ``'p'``, and ``'^'`` are interpreted as ``PPULSE``.
+"""
+RISE = 0b101
+"""Integer constant ``0b110`` for a rising transition. ``'R'``, ``'r'``, and ``'/'`` are interpreted as ``RISE``.
+"""
+FALL = 0b110
+"""Integer constant ``0b101`` for a falling transition. ``'F'``, ``'f'``, and ``'\\'`` are interpreted as ``FALL``.
+"""
 NPULSE = 0b111
+"""Integer constant ``0b111`` for negative pulse, meaning initial and final values are 1, but there is some activity
+on a signal. ``'N'``, ``'n'``, and ``'v'`` are interpreted as ``NPULSE``.
+"""
 
 
 def interpret(value):
@@ -54,9 +67,9 @@ def interpret(value):
     if value in [None, '-', 'Z', 'z']:
         return UNASSIGNED
     if value in ['R', 'r', '/']:
-        return RISING
+        return RISE
     if value in ['F', 'f', '\\']:
-        return FALLING
+        return FALL
     if value in ['P', 'p', '^']:
         return PPULSE
     if value in ['N', 'n', 'v']:
@@ -64,6 +77,110 @@ def interpret(value):
     return UNKNOWN
 
 
+_bit_in_lut = np.array([2 ** x for x in range(7, -1, -1)], dtype='uint8')
+
+
+@numba.njit
+def bit_in(a, pos):
+    return a[pos >> 3] & _bit_in_lut[pos & 7]
+
+
+def mv_cast(*args, m=8):
+    return [a if isinstance(a, MVArray) else MVArray(a, m=m) for a in args]
+
+
+def mv_getm(*args):
+    return max([a.m for a in args if isinstance(a, MVArray)] + [0]) or 8
+
+
+def _mv_not(m, out, inp):
+    np.bitwise_xor(inp, 0b11, out=out)  # this also exchanges UNASSIGNED <-> UNKNOWN
+    if m > 2:
+        np.putmask(out, (inp == UNKNOWN), UNKNOWN)  # restore UNKNOWN
+
+
+def mv_not(x1, out=None):
+    m = mv_getm(x1)
+    x1 = mv_cast(x1, m=m)[0]
+    out = out or MVArray(x1.data.shape, m=m)
+    _mv_not(m, out.data, x1.data)
+    return out
+
+
+def _mv_or(m, out, *ins):
+    if m > 2:
+        any_unknown = (ins[0] == UNKNOWN) | (ins[0] == UNASSIGNED)
+        for inp in ins[1:]: any_unknown |= (inp == UNKNOWN) | (inp == UNASSIGNED)
+        any_one = (ins[0] == ONE)
+        for inp in ins[1:]: any_one |= (inp == ONE)
+
+        out[...] = ZERO
+        np.putmask(out, any_one, ONE)
+        for inp in ins:
+            np.bitwise_or(out, inp, out=out, where=~any_one)
+        np.putmask(out, (any_unknown & ~any_one), UNKNOWN)
+    else:
+        out[...] = ZERO
+        for inp in ins: np.bitwise_or(out, inp, out=out)
+
+
+def mv_or(x1, x2, out=None):
+    m = mv_getm(x1, x2)
+    x1, x2 = mv_cast(x1, x2, m=m)
+    out = out or MVArray(np.broadcast(x1.data, x2.data).shape, m=m)
+    _mv_or(m, out.data, x1.data, x2.data)
+    return out
+
+
+def _mv_and(m, out, *ins):
+    if m > 2:
+        any_unknown = (ins[0] == UNKNOWN) | (ins[0] == UNASSIGNED)
+        for inp in ins[1:]: any_unknown |= (inp == UNKNOWN) | (inp == UNASSIGNED)
+        any_zero = (ins[0] == ZERO)
+        for inp in ins[1:]: any_zero |= (inp == ZERO)
+
+        out[...] = ONE
+        np.putmask(out, any_zero, ZERO)
+        for inp in ins:
+            np.bitwise_and(out, inp | 0b100, out=out, where=~any_zero)
+            if m > 4: np.bitwise_or(out, inp & 0b100, out=out, where=~any_zero)
+        np.putmask(out, (any_unknown & ~any_zero), UNKNOWN)
+    else:
+        out[...] = ONE
+        for inp in ins: np.bitwise_and(out, inp, out=out)
+
+
+def mv_and(x1, x2, out=None):
+    m = mv_getm(x1, x2)
+    x1, x2 = mv_cast(x1, x2, m=m)
+    out = out or MVArray(np.broadcast(x1.data, x2.data).shape, m=m)
+    _mv_and(m, out.data, x1.data, x2.data)
+    return out
+
+
+def _mv_xor(m, out, *ins):
+    if m > 2:
+        any_unknown = (ins[0] == UNKNOWN) | (ins[0] == UNASSIGNED)
+        for inp in ins[1:]: any_unknown |= (inp == UNKNOWN) | (inp == UNASSIGNED)
+
+        out[...] = ZERO
+        for inp in ins:
+            np.bitwise_xor(out, inp & 0b011, out=out)
+            if m > 4: np.bitwise_or(out, inp & 0b100, out=out)
+        np.putmask(out, any_unknown, UNKNOWN)
+    else:
+        out[...] = ZERO
+        for inp in ins: np.bitwise_xor(out, inp, out=out)
+
+
+def mv_xor(x1, x2, out=None):
+    m = mv_getm(x1, x2)
+    x1, x2 = mv_cast(x1, x2, m=m)
+    out = out or MVArray(np.broadcast(x1.data, x2.data).shape, m=m)
+    _mv_xor(m, out.data, x1.data, x2.data)
+    return out
+
+
 class MVArray:
     """An n-dimensional array of m-valued logic values.
 
@@ -71,11 +188,7 @@ class MVArray:
     interpreting 2-valued, 4-valued, and 8-valued logic values.
     Each logic value is stored as an uint8, value manipulations are cheaper than in BPArray.
 
-    Axis convention (1 axis, a single vector/pattern):
-
-    * Axis is PI/PO/FF position, the length of this axis is called "width".
-
-    Axis convention for 2 and more axes is consistent with BPArray:
+    An MVArray always has 2 or more axes:
 
     * Second-last axis is PI/PO/FF position, the length of this axis is called "width".
     * Last axis is vector/pattern, the length of this axis is called "length".
@@ -83,33 +196,43 @@ class MVArray:
     """
 
     def __init__(self, a, m=None):
-        self.m = m or 4
-        assert self.m in range(2, 256)
+        self.m = m or 8
+        assert self.m in [2, 4, 8]
 
         # Try our best to interpret given a.
         if isinstance(a, MVArray):
             self.data = a.data.copy()
             self.m = m or a.m
-        elif isinstance(a, int) or isinstance(a, tuple):
+        elif isinstance(a, int):
+            self.data = np.full((a, 1), UNASSIGNED, dtype=np.uint8)
+        elif isinstance(a, tuple):
             self.data = np.full(a, UNASSIGNED, dtype=np.uint8)
         else:
+            if isinstance(a, str):
+                a = [a]
             self.data = np.asarray(interpret(a), dtype=np.uint8)
-            if self.data.ndim > 1:
+            if self.data.ndim == 1:
+                self.data = self.data[:, np.newaxis]
+            else:
                 self.data = np.moveaxis(self.data, -2, -1)
 
         # Cast data to m-valued logic.
         if self.m == 2:
-            self.data[...] = ((self.data & 0b001) & ((self.data >> 1) & 0b001) | (self.data == RISING)) * ONE
+            self.data[...] = ((self.data & 0b001) & ((self.data >> 1) & 0b001) | (self.data == RISE)) * ONE
         elif self.m == 4:
-            self.data[...] = (self.data & 0b011) & ((self.data != FALLING) * ONE) | ((self.data == RISING) * ONE)
+            self.data[...] = (self.data & 0b011) & ((self.data != FALL) * ONE) | ((self.data == RISE) * ONE)
         elif self.m == 8:
             self.data[...] = self.data & 0b111
 
-        self.length = 1 if self.data.ndim == 1 else self.data.shape[-1]
-        self.width = len(self.data) if self.data.ndim == 1 else self.data.shape[-2]
+        self.length = self.data.shape[-1]
+        self.width = self.data.shape[-2]
 
     def __repr__(self):
-        return f'<MVArray length={self.length} width={self.width} m={self.m} bytes={self.data.nbytes}>'
+        return f'<MVArray length={self.length} width={self.width} m={self.m} nbytes={self.data.nbytes}>'
+
+    def __str__(self):
+        chars = ["0", "X", "-", "1", "P", "R", "F", "N"]
+        return str([''.join(chars[v] for v in self.data[:, idx]) for idx in range(self.length)])
 
 
 class BPArray:

src/kyupy/logic_sim.py

@@ -1,9 +1,10 @@
 import numpy as np
+
 from . import packed_vectors
 
 
 class LogicSim:
-    """A bit-parallel naive combinational logic simulator supporting 1, 4, or 8-valued logics.
+    """A bit-parallel naïve combinational simulator for 2-, 4-, or 8-valued logic.
     """
     def __init__(self, circuit, nvectors=1, vdim=1):
         self.circuit = circuit
@@ -52,13 +53,13 @@ class LogicSim:
             t = t.replace('__const0__', 'const0')
             t = t.replace('__const1__', 'const1')
             t = t.replace('tieh', 'const1')
-            # t = t.replace('xor', 'or').replace('xnor', 'nor')
             fcts = [f for n, f in known_fct if t.startswith(n)]
             if len(fcts) < 1:
                 raise ValueError(f'Unknown node kind {n.kind}')
             self.node_fct.append(fcts[0])
 
     def assign(self, stimuli):
+        """Assign stimuli to the primary inputs and state-elements (flip-flops)."""
         if isinstance(stimuli, packed_vectors.PackedVectors):
             stimuli = stimuli.bits
         for (stim, node) in zip(stimuli, self.interface):
@@ -78,6 +79,7 @@ class LogicSim:
                         self.state_epoch[line.reader.index] = self.epoch
 
     def capture(self, responses):
+        """Capture the current values at the primary outputs and in the state-elements (flip-flops)."""
         if isinstance(responses, packed_vectors.PackedVectors):
             responses = responses.bits
         for (resp, node) in zip(responses, self.interface):
@@ -85,6 +87,7 @@ class LogicSim:
             resp[...] = self.state[node.ins[0].index]
 
     def propagate(self):
+        """Propagate the input values towards the outputs (Perform all logic operations in topological order)."""
         for node in self.circuit.topological_order():
             if self.state_epoch[node.index] != self.epoch: continue
             inputs = [self.state[line.index] if line else self.zero for line in node.ins]

src/kyupy/packed_vectors.py

@@ -1,5 +1,6 @@
 import numpy as np
-from .bittools import popcount, bit_in
+from . import popcount
+from .logic import bit_in
 
 
 class PackedVectors:

src/kyupy/sdf.py

@@ -1,14 +1,28 @@
+"""A simple and incomplete parser for the Standard Delay Format (SDF).
+
+The main purpose of this parser is to extract pin-to-pin delay and interconnect delay information from SDF files.
+Sophisticated timing specifications (timing checks, conditional delays, etc.) are currently not supported.
+
+The functions :py:func:`load` and :py:func:`read` return an intermediate representation (:class:`DelayFile` object).
+Call :py:func:`DelayFile.annotation` to match the intermediate representation to a given circuit.
+
+"""
+
+from collections import namedtuple
+
 import numpy as np
 from lark import Lark, Transformer
-from collections import namedtuple
-from . import log
-import gzip
+
+from . import log, readtext
+
 
 Interconnect = namedtuple('Interconnect', ['orig', 'dest', 'r', 'f'])
 IOPath = namedtuple('IOPath', ['ipin', 'opin', 'r', 'f'])
 
 
 class DelayFile:
+    """An intermediate representation of an SDF file.
+    """
     def __init__(self, name, cells):
         self.name = name
         if None in cells:
@@ -22,26 +36,26 @@ class DelayFile:
                '\n'.join(str(i) for i in self.interconnects)
 
     def annotation(self, circuit, pin_index_f, dataset=1, interconnect=True, ffdelays=True):
-        """
-        Constructs an 3-dimensional array with timing data for each line in `circuit`.
-        Dimension 1 of the returned array is the line index.
-        Dimension 2 is the type of timing data: 0:`delay`, 1:`pulse rejection limit`.
-        Dimension 3 is the polarity at the output of the reading node: 0:`rising`, 1:`falling`.
-
-        The polarity for pulse rejection is determined by the latter transition of the pulse.
-        E.g., timing[42,1,0] is the rejection limit of a negative pulse at the output of the reader of line 42.
+        """Constructs an 3-dimensional ndarray with timing data for each line in ``circuit``.
 
         An IOPATH delay for a node is annotated to the line connected to the input pin specified in the IOPATH.
 
         Currently, only ABSOLUTE IOPATH and INTERCONNECT delays are supported.
         Pulse rejection limits are derived from absolute delays, explicit declarations (PATHPULSE etc.) are ignored.
 
-
+        :param circuit:
+        :param pin_index_f:
         :param ffdelays:
         :param interconnect:
-        :param pin_index_f:
-        :param circuit:
         :type dataset: int or tuple
+        :return: A 3-dimensional ndarray with timing data.
+
+            * Axis 0: line index.
+            * Axis 1: type of timing data: 0=`delay`, 1=`pulse rejection limit`.
+            * Axis 2: The polarity of the output transition of the reading node: 0=`rising`, 1=`falling`.
+
+            The polarity for pulse rejection is determined by the latter transition of the pulse.
+            E.g., timing[42,1,0] is the rejection limit of a negative pulse at the output of the reader of line 42.
         """
         def select_del(_delvals, idx):
             if type(dataset) is tuple:
@@ -170,7 +184,6 @@ class SdfTransformer(Transformer):
         return DelayFile(name, cells)
 
 
-def parse(sdf):
 grammar = r"""
     start: "(DELAYFILE" ( "(SDFVERSION" _NOB ")"
         | "(DESIGN" "\"" NAME "\"" ")"
@@ -201,13 +214,16 @@ def parse(sdf):
     %ignore ( /\r?\n/ | COMMENT )+
     %ignore /[\t\f ]+/
     """
-    if '\n' not in str(sdf):  # One line?: Assuming it is a file name.
-        if str(sdf).endswith('.gz'):
-            with gzip.open(sdf, 'rt') as f:
-                text = f.read()
-        else:
-            with open(sdf, 'r') as f:
-                text = f.read()
-    else:
-        text = str(sdf)
+
+
+def parse(text):
+    """Parses the given ``text`` and returns a :class:`DelayFile` object."""
     return Lark(grammar, parser="lalr", transformer=SdfTransformer()).parse(text)
+
+
+def load(file):
+    """Parses the contents of ``file`` and returns a :class:`DelayFile` object.
+
+    The given file may be gzip compressed.
+    """
+    return parse(readtext(file))

src/kyupy/stil.py

@@ -1,9 +1,20 @@
+"""A simple and incomplete parser for the Standard Test Interface Language (STIL).
+
+The main purpose of this parser is to load scan pattern sets from STIL files.
+It supports only a very limited subset of STIL.
+
+The functions :py:func:`load` and :py:func:`read` return an intermediate representation (:class:`StilFile` object).
+Call :py:func:`StilFile.tests4v`, :py:func:`StilFile.tests8v`, or :py:func:`StilFile.responses4v` to
+obtain the appropriate vector sets.
+"""
+
 from lark import Lark, Transformer
 from collections import namedtuple
 import re
-import gzip
+
 from .packed_vectors import PackedVectors
 from .logic_sim import LogicSim
+from . import readtext
 
 
 Call = namedtuple('Call', ['name', 'parameters'])
@@ -11,6 +22,8 @@ ScanPattern = namedtuple('ScanPattern', ['load', 'launch', 'capture', 'unload'])
 
 
 class StilFile:
+    """An intermediate representation of a STIL file.
+    """
     def __init__(self, version, signal_groups, scan_chains, calls):
         self.version = version
         self.signal_groups = signal_groups
@@ -21,7 +34,7 @@ class StilFile:
         self.patterns = []
         launch = {}
         capture = {}
-        load = {}
+        sload = {}
         for call in self.calls:
             if call.name == 'load_unload':
                 unload = {}
@@ -29,13 +42,13 @@ class StilFile:
                     if so_port in call.parameters:
                         unload[so_port] = call.parameters[so_port].replace('\n', '')
                 if len(launch) > 0:
-                    self.patterns.append(ScanPattern(load, launch, capture, unload))
+                    self.patterns.append(ScanPattern(sload, launch, capture, unload))
                     capture = {}
                     launch = {}
-                load = {}
+                sload = {}
                 for si_port in self.si_ports:
                     if si_port in call.parameters:
-                        load[si_port] = call.parameters[si_port].replace('\n', '')
+                        sload[si_port] = call.parameters[si_port].replace('\n', '')
             if call.name.endswith('_launch') or call.name.endswith('_capture'):
                 if len(launch) == 0:
                     launch = dict((k, v.replace('\n', '')) for k, v in call.parameters.items())
@@ -73,8 +86,12 @@ class StilFile:
             scan_inversions[chain[-1]] = scan_out_inversion
         return interface, pi_map, po_map, scan_maps, scan_inversions
         
-    def tests(self, c):
-        interface, pi_map, po_map, scan_maps, scan_inversions = self._maps(c)
+    def tests4v(self, circuit):
+        """Assembles and returns a scan test pattern set in 4-valued logic for given circuit.
+
+        This function assumes a static (stuck-at fault) test.
+        """
+        interface, pi_map, po_map, scan_maps, scan_inversions = self._maps(circuit)
         tests = PackedVectors(len(self.patterns), len(interface), 2)
         for i, p in enumerate(self.patterns):
             for si_port in self.si_ports.keys():
@@ -82,15 +99,21 @@ class StilFile:
             tests.set_values(i, p.launch['_pi'], pi_map)
         return tests
 
-    def tests8v(self, c):
-        interface, pi_map, po_map, scan_maps, scan_inversions = self._maps(c)
+    def tests8v(self, circuit):
+        """Assembles and returns a scan test pattern set in 8-valued logic for given circuit.
+
+        This function assumes a launch-on-capture (LoC) delay test.
+        It performs a logic simulation to obtain the first capture pattern (the one that launches the
+        delay test) and assembles the test pattern set from from pairs for initialization- and launch-patterns.
+        """
+        interface, pi_map, po_map, scan_maps, scan_inversions = self._maps(circuit)
         init = PackedVectors(len(self.patterns), len(interface), 2)
         for i, p in enumerate(self.patterns):
             # init.set_values(i, '0' * len(interface))
             for si_port in self.si_ports.keys():
                 init.set_values(i, p.load[si_port], scan_maps[si_port], scan_inversions[si_port])
             init.set_values(i, p.launch['_pi'], pi_map)
-        sim4v = LogicSim(c, len(init), 2)
+        sim4v = LogicSim(circuit, len(init), 2)
         sim4v.assign(init)
         sim4v.propagate()
         launch = init.copy()
@@ -105,8 +128,9 @@ class StilFile:
         
         return PackedVectors.from_pair(init, launch)
                 
-    def responses(self, c):
-        interface, pi_map, po_map, scan_maps, scan_inversions = self._maps(c)
+    def responses4v(self, circuit):
+        """Assembles and returns a scan test response pattern set in 4-valued logic for given circuit."""
+        interface, pi_map, po_map, scan_maps, scan_inversions = self._maps(circuit)
         resp = PackedVectors(len(self.patterns), len(interface), 2)
         for i, p in enumerate(self.patterns):
             if len(p.capture) > 0:
@@ -162,7 +186,6 @@ class StilTransformer(Transformer):
         return StilFile(float(args[0]), self._signal_groups, self._scan_chains, self._calls)
 
 
-def parse(stil):
 grammar = r"""
     start: "STIL" FLOAT _ignore _block*
     _block: signal_groups | scan_structures | pattern
@@ -203,50 +226,16 @@ def parse(stil):
     _NOB: /[^{}]+/
     %ignore ( /\r?\n/ | "//" /[^\n]*/ | /[\t\f ]/ )+
     """
-    if '\n' not in str(stil):  # One line?: Assuming it is a file name.
-        if str(stil).endswith('.gz'):
-            with gzip.open(stil, 'rt') as f:
-                text = f.read()
-        else:
-            with open(stil, 'r') as f:
-                text = f.read()
-    else:
-        text = str(stil)
-    return Lark(grammar, parser="lalr", transformer=StilTransformer()).parse(text)
 
 
-def extract_scan_pattens(stil_calls):
-    pats = []
-    pi = None
-    scan_in = None
-    for call in stil_calls:
-        if call.name == 'load_unload':
-            scan_out = call.parameters.get('Scan_Out')
-            if scan_out is not None:
-                scan_out = scan_out.replace('\n', '')
-            if pi: pats.append(ScanPattern(scan_in, pi, None, scan_out))
-            scan_in = call.parameters.get('Scan_In')
-            if scan_in is not None:
-                scan_in = scan_in.replace('\n', '')
-        if call.name == 'allclock_capture':
-            pi = call.parameters['_pi'].replace('\n', '')
-    return pats
-
-
-def match_patterns(stil_file, pats, interface):    
-    intf_pos = dict([(n.name, i) for i, n in enumerate(interface)])
-    pi_map = [intf_pos[n] for n in stil_file.signal_groups['_pi']]
-    scan_map = [intf_pos[re.sub(r'b..\.', '', n)] for n in reversed(stil_file.scan_chains['1'])]
-    # print(scan_map)
-    tests = PackedVectors(len(pats), len(interface), 2)
-    for i, p in enumerate(pats):
-        tests.set_values(i, p.scan_in, scan_map)
-        tests.set_values(i, p.pi, pi_map)
+def parse(text):
+    """Parses the given ``text`` and returns a :class:`StilFile` object."""
+    return Lark(grammar, parser="lalr", transformer=StilTransformer()).parse(text)
 
-    resp = PackedVectors(len(pats), len(interface), 2)
-    for i, p in enumerate(pats):
-        resp.set_values(i, p.pi, pi_map)
-        resp.set_values(i, p.scan_out, scan_map)
 
-    return tests, resp
+def load(file):
+    """Parses the contents of ``file`` and returns a :class:`StilFile` object.
 
+    The given file may be gzip compressed.
+    """
+    return parse(readtext(file))

src/kyupy/verilog.py

@@ -1,8 +1,14 @@
+"""A simple and incomplete parser for Verilog files.
+
+The main purpose of this parser is to load synthesized, non-hierarchical (flat) gate-level netlists.
+It supports only a very limited subset of Verilog.
+"""
+
 from collections import namedtuple
-import gzip
 
 from lark import Lark, Transformer
 
+from . import readtext
 from .circuit import Circuit, Node, Line
 from .saed import pin_index, pin_is_output
 
@@ -152,22 +158,21 @@ grammar = """
     """
 
 
-def loads(s, *, branchforks=False):
-    return Lark(grammar, parser="lalr", transformer=VerilogTransformer(branchforks)).parse(s)
+def parse(text, *, branchforks=False):
+    """Parses the given ``text`` as Verilog code.
 
+    :param text: A string with Verilog code.
+    :param branchforks: If set to ``True``, the returned circuit will include additional `forks` on each fanout branch.
+        These forks are needed to correctly annotate interconnect delays
+        (see :py:func:`kyupy.sdf.DelayFile.annotation`).
+    :return: A :class:`~kyupy.circuit.Circuit` object.
+    """
+    return Lark(grammar, parser="lalr", transformer=VerilogTransformer(branchforks)).parse(text)
 
-def load(fp, *, branchforks=False):
-    return loads(fp.read(), branchforks=branchforks)
 
+def load(file, *args, **kwargs):
+    """Parses the contents of ``file`` as Verilog code.
 
-def parse(verilog, branchforks=False):
-    if '\n' not in str(verilog):  # One line?: Assuming it is a file name.
-        if str(verilog).endswith('.gz'):
-            with gzip.open(verilog, 'rt') as f:
-                text = f.read()
-        else:
-            with open(verilog, 'r') as f:
-                text = f.read()
-    else:
-        text = str(verilog)
-    return loads(text, branchforks=branchforks)
+    The given file may be gzip compressed. Takes the same keyword arguments as :py:func:`parse`.
+    """
+    return parse(readtext(file), *args, **kwargs)

src/kyupy/wave_sim.py

@@ -1,8 +1,24 @@
+"""High-Throughput combinational logic timing simulators.
+
+These simulators work similarly to :py:class:`kyupy.logic_sim.LogicSim`.
+They propagate values through the combinational circuit from (pseudo) primary inputs to (pseudo) primary outputs.
+Instead of propagating logic values, these simulators propagate signal histories (waveforms).
+They are designed to run many simulations in parallel and while their latencies are quite high, they achieve
+high throughput performance.
+
+The simulators are not event-based and are not capable of simulating sequential circuits directly.
+
+Two simulators are available: :py:class:`WaveSim` runs on the CPU, and the derived class
+:py:class:`WaveSimCuda` runs on the GPU.
+"""
+
 import math
 from bisect import bisect, insort_left
 
 import numpy as np
+
 from . import numba
+from . import cuda
 
 
 TMAX = np.float32(2 ** 127)  # almost np.PINF for 32-bit floating point values
@@ -77,6 +93,7 @@ class Heap:
 
 
 class WaveSim:
+    """A waveform-based combinational logic timing simulator."""
     def __init__(self, circuit, timing, sims=8, wavecaps=16, strip_forks=False, keep_waveforms=True):
         self.circuit = circuit
         self.sims = sims
@@ -519,3 +536,313 @@ def wave_eval(op, state, sat, st_idx, line_times, sd=0.0, seed=0):
         state[z_mem + z_cur, st_idx] = a if a > b else b  # propagate overflow flags by storing biggest TMAX from input
         
     return overflows
+
+
+class WaveSimCuda(WaveSim):
+    """A GPU-accelerated waveform-based combinational logic timing simulator."""
+    def __init__(self, circuit, timing, sims=8, wavecaps=16, strip_forks=False, keep_waveforms=True):
+        super().__init__(circuit, timing, sims, wavecaps, strip_forks, keep_waveforms)
+
+        self.tdata = np.zeros((len(self.interface), 3, (sims - 1) // 8 + 1), dtype='uint8')
+
+        self.d_state = cuda.to_device(self.state)
+        self.d_sat = cuda.to_device(self.sat)
+        self.d_ops = cuda.to_device(self.ops)
+        self.d_timing = cuda.to_device(self.timing)
+        self.d_tdata = cuda.to_device(self.tdata)
+        self.d_cdata = cuda.to_device(self.cdata)
+
+        self._block_dim = (32, 16)
+
+    def get_line_delay(self, line, polarity):
+        return self.d_timing[line, 0, polarity]
+
+    def set_line_delay(self, line, polarity, delay):
+        self.d_timing[line, 0, polarity] = delay
+
+    def assign(self, vectors, time=0.0, offset=0):
+        assert (offset % 8) == 0
+        byte_offset = offset // 8
+        assert byte_offset < vectors.bits.shape[-1]
+        pdim = min(vectors.bits.shape[-1] - byte_offset, self.tdata.shape[-1])
+
+        self.tdata[..., 0:pdim] = vectors.bits[..., byte_offset:pdim + byte_offset]
+        if vectors.vdim == 1:
+            self.tdata[:, 1, 0:pdim] = ~self.tdata[:, 1, 0:pdim]
+            self.tdata[:, 2, 0:pdim] = 0
+        cuda.to_device(self.tdata, to=self.d_tdata)
+
+        grid_dim = self._grid_dim(self.sims, len(self.interface))
+        assign_kernel[grid_dim, self._block_dim](self.d_state, self.d_sat, self.ppi_offset,
+                                                 len(self.interface), self.d_tdata, time)
+
+    def _grid_dim(self, x, y):
+        gx = math.ceil(x / self._block_dim[0])
+        gy = math.ceil(y / self._block_dim[1])
+        return gx, gy
+
+    def propagate(self, sims=None, sd=0.0, seed=1):
+        if sims is None:
+            sims = self.sims
+        else:
+            sims = min(sims, self.sims)
+        for op_start, op_stop in zip(self.level_starts, self.level_stops):
+            grid_dim = self._grid_dim(sims, op_stop - op_start)
+            wave_kernel[grid_dim, self._block_dim](self.d_ops, op_start, op_stop, self.d_state, self.sat, int(0),
+                                                   sims, self.d_timing, sd, seed)
+        cuda.synchronize()
+        self.lst_eat_valid = False
+
+    def wave(self, line, vector):
+        if line < 0:
+            return None
+        mem, wcap, _ = self.sat[line]
+        if mem < 0:
+            return None
+        return self.d_state[mem:mem + wcap, vector]
+
+    def capture(self, time=TMAX, sd=0, seed=1, cdata=None, offset=0):
+        grid_dim = self._grid_dim(self.sims, len(self.interface))
+        capture_kernel[grid_dim, self._block_dim](self.d_state, self.d_sat, self.ppo_offset,
+                                                  self.d_cdata, time, sd * math.sqrt(2), seed)
+        self.cdata[...] = self.d_cdata
+        if cdata is not None:
+            assert offset < cdata.shape[1]
+            cap_dim = min(cdata.shape[1] - offset, self.sims)
+            cdata[:, offset:cap_dim + offset] = self.cdata[:, 0:cap_dim]
+        self.lst_eat_valid = True
+        return self.cdata
+
+    def reassign(self, time=0.0):
+        grid_dim = self._grid_dim(self.sims, len(self.interface))
+        reassign_kernel[grid_dim, self._block_dim](self.d_state, self.d_sat, self.ppi_offset, self.ppo_offset,
+                                                   self.d_cdata, time)
+        cuda.synchronize()
+
+    def wavecaps(self):
+        gx = math.ceil(len(self.circuit.lines) / 512)
+        wavecaps_kernel[gx, 512](self.d_state, self.d_sat, self.sims)
+        self.sat[...] = self.d_sat
+        return self.sat[..., 2]
+
+
+@cuda.jit()
+def wavecaps_kernel(state, sat, sims):
+    idx = cuda.grid(1)
+    if idx >= len(sat): return
+
+    lidx, lcap, _ = sat[idx]
+    if lidx < 0: return
+
+    wcap = 0
+    for sidx in range(sims):
+        for tidx in range(lcap):
+            t = state[lidx + tidx, sidx]
+            if tidx > wcap:
+                wcap = tidx
+            if t >= TMAX: break
+
+    sat[idx, 2] = wcap + 1
+
+
+@cuda.jit()
+def reassign_kernel(state, sat, ppi_offset, ppo_offset, cdata, ppi_time):
+    vector, y = cuda.grid(2)
+    if vector >= state.shape[-1]: return
+    if ppo_offset + y >= len(sat): return
+
+    ppo, ppo_cap, _ = sat[ppo_offset + y]
+    ppi, ppi_cap, _ = sat[ppi_offset + y]
+    if ppo < 0: return
+    if ppi < 0: return
+
+    ppo_val = int(cdata[y, vector, 1])
+    ppi_val = int(0)
+    for tidx in range(ppi_cap):
+        t = state[ppi + tidx, vector]
+        if t >= TMAX: break
+        ppi_val ^= 1
+
+    # make new waveform at PPI
+    toggle = 0
+    if ppi_val:
+        state[ppi + toggle, vector] = TMIN
+        toggle += 1
+    if ppi_val != ppo_val:
+        state[ppi + toggle, vector] = ppi_time
+        toggle += 1
+    state[ppi + toggle, vector] = TMAX
+
+
+@cuda.jit()
+def capture_kernel(state, sat, ppo_offset, cdata, time, s_sqrt2, seed):
+    x, y = cuda.grid(2)
+    if ppo_offset + y >= len(sat): return
+    line, tdim, _ = sat[ppo_offset + y]
+    if line < 0: return
+    if x >= state.shape[-1]: return
+    vector = x
+    m = 0.5
+    acc = 0.0
+    eat = TMAX
+    lst = TMIN
+    tog = 0
+    ovl = 0
+    val = int(0)
+    final = int(0)
+    for tidx in range(tdim):
+        t = state[line + tidx, vector]
+        if t >= TMAX:
+            if t == TMAX_OVL:
+                ovl = 1
+            break
+        m = -m
+        final ^= 1
+        if t < time:
+            val ^= 1
+        if t <= TMIN: continue
+        if s_sqrt2 > 0:
+            acc += m * (1 + math.erf((t - time) / s_sqrt2))
+        eat = min(eat, t)
+        lst = max(lst, t)
+        tog += 1
+    if s_sqrt2 > 0:
+        if m < 0:
+            acc += 1
+        if acc >= 0.99:
+            val = 1
+        elif acc > 0.01:
+            seed = (seed << 4) + (vector << 20) + (y << 1)
+            seed = int(0xDEECE66D) * seed + 0xB
+            seed = int(0xDEECE66D) * seed + 0xB
+            rnd = float((seed >> 8) & 0xffffff) / float(1 << 24)
+            val = rnd < acc
+        else:
+            val = 0
+    else:
+        acc = val
+
+    cdata[y, vector, 0] = acc
+    cdata[y, vector, 1] = val
+    cdata[y, vector, 2] = final
+    cdata[y, vector, 3] = (val != final)
+    cdata[y, vector, 4] = eat
+    cdata[y, vector, 5] = lst
+    cdata[y, vector, 6] = ovl
+
+
+@cuda.jit()
+def assign_kernel(state, sat, ppi_offset, intf_len, tdata, time):
+    x, y = cuda.grid(2)
+    if y >= intf_len: return
+    line = sat[ppi_offset + y, 0]
+    if line < 0: return
+    sdim = state.shape[-1]
+    if x >= sdim: return
+    vector = x
+    a0 = tdata[y, 0, vector // 8]
+    a1 = tdata[y, 1, vector // 8]
+    a2 = tdata[y, 2, vector // 8]
+    m = np.uint8(1 << (7 - (vector % 8)))
+    toggle = 0
+    if a0 & m:
+        state[line + toggle, x] = TMIN
+        toggle += 1
+    if (a2 & m) and ((a0 & m) == (a1 & m)):
+        state[line + toggle, x] = time
+        toggle += 1
+    state[line + toggle, x] = TMAX
+
+
+@cuda.jit(device=True)
+def rand_gauss_dev(seed, sd):
+    clamp = 0.5
+    if sd <= 0.0:
+        return 1.0
+    while True:
+        x = -6.0
+        for i in range(12):
+            seed = int(0xDEECE66D) * seed + 0xB
+            x += float((seed >> 8) & 0xffffff) / float(1 << 24)
+        x *= sd
+        if abs(x) <= clamp:
+            break
+    return x + 1.0
+
+
+@cuda.jit()
+def wave_kernel(ops, op_start, op_stop, state, sat, st_start, st_stop, line_times, sd, seed):
+    x, y = cuda.grid(2)
+    st_idx = st_start + x
+    op_idx = op_start + y
+    if st_idx >= st_stop: return
+    if op_idx >= op_stop: return
+    lut = ops[op_idx, 0]
+    z_idx = ops[op_idx, 1]
+    a_idx = ops[op_idx, 2]
+    b_idx = ops[op_idx, 3]
+    overflows = int(0)
+
+    _seed = (seed << 4) + (z_idx << 20) + (st_idx << 1)
+
+    a_mem = sat[a_idx, 0]
+    b_mem = sat[b_idx, 0]
+    z_mem, z_cap, _ = sat[z_idx]
+
+    a_cur = int(0)
+    b_cur = int(0)
+    z_cur = lut & 1
+    if z_cur == 1:
+        state[z_mem, st_idx] = TMIN
+
+    a = state[a_mem, st_idx] + line_times[a_idx, 0, z_cur] * rand_gauss_dev(_seed ^ a_mem ^ z_cur, sd)
+    b = state[b_mem, st_idx] + line_times[b_idx, 0, z_cur] * rand_gauss_dev(_seed ^ b_mem ^ z_cur, sd)
+
+    previous_t = TMIN
+
+    current_t = min(a, b)
+    inputs = int(0)
+
+    while current_t < TMAX:
+        z_val = z_cur & 1
+        if b < a:
+            b_cur += 1
+            b = state[b_mem + b_cur, st_idx]
+            b += line_times[b_idx, 0, z_val ^ 1] * rand_gauss_dev(_seed ^ b_mem ^ z_val ^ 1, sd)
+            thresh = line_times[b_idx, 1, z_val] * rand_gauss_dev(_seed ^ b_mem ^ z_val, sd)
+            inputs ^= 2
+            next_t = b
+        else:
+            a_cur += 1
+            a = state[a_mem + a_cur, st_idx]
+            a += line_times[a_idx, 0, z_val ^ 1] * rand_gauss_dev(_seed ^ a_mem ^ z_val ^ 1, sd)
+            thresh = line_times[a_idx, 1, z_val] * rand_gauss_dev(_seed ^ a_mem ^ z_val, sd)
+            inputs ^= 1
+            next_t = a
+
+        if (z_cur & 1) != ((lut >> inputs) & 1):
+            # we generate a toggle in z_mem, if:
+            #   ( it is the first toggle in z_mem OR
+            #   following toggle is earlier OR
+            #   pulse is wide enough ) AND enough space in z_mem.
+            if z_cur == 0 or next_t < current_t or (current_t - previous_t) > thresh:
+                if z_cur < (z_cap - 1):
+                    state[z_mem + z_cur, st_idx] = current_t
+                    previous_t = current_t
+                    z_cur += 1
+                else:
+                    overflows += 1
+                    previous_t = state[z_mem + z_cur - 1, st_idx]
+                    z_cur -= 1
+            else:
+                z_cur -= 1
+                if z_cur > 0:
+                    previous_t = state[z_mem + z_cur - 1, st_idx]
+                else:
+                    previous_t = TMIN
+        current_t = min(a, b)
+
+    if overflows > 0:
+        state[z_mem + z_cur, st_idx] = TMAX_OVL
+    else:
+        state[z_mem + z_cur, st_idx] = a if a > b else b  # propagate overflow flags by storing biggest TMAX from input

src/kyupy/wave_sim_cuda.py

@@ -1,317 +0,0 @@
-import numpy as np
-import math
-from .wave_sim import WaveSim
-from . import cuda
-
-TMAX = np.float32(2 ** 127)  # almost np.PINF for 32-bit floating point values
-TMAX_OVL = np.float32(1.1 * 2 ** 127)  # almost np.PINF with overflow mark
-TMIN = np.float32(-2 ** 127)  # almost np.NINF for 32-bit floating point values
-
-
-class WaveSimCuda(WaveSim):
-    def __init__(self, circuit, timing, sims=8, wavecaps=16, strip_forks=False, keep_waveforms=True):
-        super().__init__(circuit, timing, sims, wavecaps, strip_forks, keep_waveforms)
-
-        self.tdata = np.zeros((len(self.interface), 3, (sims - 1) // 8 + 1), dtype='uint8')
-
-        self.d_state = cuda.to_device(self.state)
-        self.d_sat = cuda.to_device(self.sat)
-        self.d_ops = cuda.to_device(self.ops)
-        self.d_timing = cuda.to_device(self.timing)
-        self.d_tdata = cuda.to_device(self.tdata)
-        self.d_cdata = cuda.to_device(self.cdata)
-
-        self._block_dim = (32, 16)
-
-    def get_line_delay(self, line, polarity):
-        return self.d_timing[line, 0, polarity]
-
-    def set_line_delay(self, line, polarity, delay):
-        self.d_timing[line, 0, polarity] = delay
-
-    def assign(self, vectors, time=0.0, offset=0):
-        assert (offset % 8) == 0
-        byte_offset = offset // 8
-        assert byte_offset < vectors.bits.shape[-1]
-        pdim = min(vectors.bits.shape[-1] - byte_offset, self.tdata.shape[-1])
-
-        self.tdata[..., 0:pdim] = vectors.bits[..., byte_offset:pdim + byte_offset]
-        if vectors.vdim == 1:
-            self.tdata[:, 1, 0:pdim] = ~self.tdata[:, 1, 0:pdim]
-            self.tdata[:, 2, 0:pdim] = 0
-        cuda.to_device(self.tdata, to=self.d_tdata)
-
-        grid_dim = self._grid_dim(self.sims, len(self.interface))
-        assign_kernel[grid_dim, self._block_dim](self.d_state, self.d_sat, self.ppi_offset,
-                                                 len(self.interface), self.d_tdata, time)
-
-    def _grid_dim(self, x, y):
-        gx = math.ceil(x / self._block_dim[0])
-        gy = math.ceil(y / self._block_dim[1])
-        return gx, gy
-
-    def propagate(self, sims=None, sd=0.0, seed=1):
-        if sims is None:
-            sims = self.sims
-        else:
-            sims = min(sims, self.sims)
-        for op_start, op_stop in zip(self.level_starts, self.level_stops):
-            grid_dim = self._grid_dim(sims, op_stop - op_start)
-            wave_kernel[grid_dim, self._block_dim](self.d_ops, op_start, op_stop, self.d_state, self.sat, int(0),
-                                                   sims, self.d_timing, sd, seed)
-        cuda.synchronize()
-        self.lst_eat_valid = False
-
-    def wave(self, line, vector):
-        if line < 0:
-            return None
-        mem, wcap, _ = self.sat[line]
-        if mem < 0:
-            return None
-        return self.d_state[mem:mem + wcap, vector]
-    
-    def capture(self, time=TMAX, sd=0, seed=1, cdata=None, offset=0):
-        grid_dim = self._grid_dim(self.sims, len(self.interface))
-        capture_kernel[grid_dim, self._block_dim](self.d_state, self.d_sat, self.ppo_offset,
-                                                  self.d_cdata, time, sd * math.sqrt(2), seed)
-        self.cdata[...] = self.d_cdata
-        if cdata is not None:
-            assert offset < cdata.shape[1]
-            cap_dim = min(cdata.shape[1] - offset, self.sims)
-            cdata[:, offset:cap_dim + offset] = self.cdata[:, 0:cap_dim]
-        self.lst_eat_valid = True
-        return self.cdata
-
-    def reassign(self, time=0.0):
-        grid_dim = self._grid_dim(self.sims, len(self.interface))
-        reassign_kernel[grid_dim, self._block_dim](self.d_state, self.d_sat, self.ppi_offset, self.ppo_offset,
-                                                   self.d_cdata, time)
-        cuda.synchronize()
-        
-    def wavecaps(self):
-        gx = math.ceil(len(self.circuit.lines) / 512)
-        wavecaps_kernel[gx, 512](self.d_state, self.d_sat, self.sims)
-        self.sat[...] = self.d_sat
-        return self.sat[..., 2]
-
-
-@cuda.jit()
-def wavecaps_kernel(state, sat, sims):
-    idx = cuda.grid(1)
-    if idx >= len(sat): return
-    
-    lidx, lcap, _ = sat[idx]
-    if lidx < 0: return
-    
-    wcap = 0
-    for sidx in range(sims):
-        for tidx in range(lcap):
-            t = state[lidx + tidx, sidx]
-            if tidx > wcap:
-                wcap = tidx
-            if t >= TMAX: break
-
-    sat[idx, 2] = wcap + 1
-    
-    
-@cuda.jit()
-def reassign_kernel(state, sat, ppi_offset, ppo_offset, cdata, ppi_time):
-    vector, y = cuda.grid(2)
-    if vector >= state.shape[-1]: return
-    if ppo_offset + y >= len(sat): return
-
-    ppo, ppo_cap, _ = sat[ppo_offset + y]
-    ppi, ppi_cap, _ = sat[ppi_offset + y]
-    if ppo < 0: return
-    if ppi < 0: return
-
-    ppo_val = int(cdata[y, vector, 1])
-    ppi_val = int(0)
-    for tidx in range(ppi_cap):
-        t = state[ppi + tidx, vector]
-        if t >= TMAX: break
-        ppi_val ^= 1
-    
-    # make new waveform at PPI
-    toggle = 0
-    if ppi_val:
-        state[ppi + toggle, vector] = TMIN
-        toggle += 1
-    if ppi_val != ppo_val:
-        state[ppi + toggle, vector] = ppi_time
-        toggle += 1
-    state[ppi + toggle, vector] = TMAX
-
-
-@cuda.jit()
-def capture_kernel(state, sat, ppo_offset, cdata, time, s_sqrt2, seed):
-    x, y = cuda.grid(2)
-    if ppo_offset + y >= len(sat): return
-    line, tdim, _ = sat[ppo_offset + y]
-    if line < 0: return
-    if x >= state.shape[-1]: return
-    vector = x
-    m = 0.5
-    acc = 0.0
-    eat = TMAX
-    lst = TMIN
-    tog = 0
-    ovl = 0
-    val = int(0)
-    final = int(0)
-    for tidx in range(tdim):
-        t = state[line + tidx, vector]
-        if t >= TMAX:
-            if t == TMAX_OVL:
-                ovl = 1
-            break
-        m = -m
-        final ^= 1
-        if t < time:
-            val ^= 1
-        if t <= TMIN: continue
-        if s_sqrt2 > 0:
-            acc += m * (1 + math.erf((t - time) / s_sqrt2))
-        eat = min(eat, t)
-        lst = max(lst, t)
-        tog += 1
-    if s_sqrt2 > 0:
-        if m < 0:
-            acc += 1
-        if acc >= 0.99:
-            val = 1
-        elif acc > 0.01:
-            seed = (seed << 4) + (vector << 20) + (y << 1)
-            seed = int(0xDEECE66D) * seed + 0xB
-            seed = int(0xDEECE66D) * seed + 0xB
-            rnd = float((seed >> 8) & 0xffffff) / float(1 << 24)
-            val = rnd < acc
-        else:
-            val = 0
-    else:
-        acc = val
-        
-    cdata[y, vector, 0] = acc
-    cdata[y, vector, 1] = val
-    cdata[y, vector, 2] = final
-    cdata[y, vector, 3] = (val != final)
-    cdata[y, vector, 4] = eat
-    cdata[y, vector, 5] = lst
-    cdata[y, vector, 6] = ovl
-
-
-@cuda.jit()
-def assign_kernel(state, sat, ppi_offset, intf_len, tdata, time):
-    x, y = cuda.grid(2)
-    if y >= intf_len: return
-    line = sat[ppi_offset + y, 0]
-    if line < 0: return
-    sdim = state.shape[-1]
-    if x >= sdim: return
-    vector = x
-    a0 = tdata[y, 0, vector // 8]
-    a1 = tdata[y, 1, vector // 8]
-    a2 = tdata[y, 2, vector // 8]
-    m = np.uint8(1 << (7 - (vector % 8)))
-    toggle = 0
-    if a0 & m:
-        state[line + toggle, x] = TMIN
-        toggle += 1
-    if (a2 & m) and ((a0 & m) == (a1 & m)):
-        state[line + toggle, x] = time
-        toggle += 1
-    state[line + toggle, x] = TMAX
-
-
-@cuda.jit(device=True)
-def rand_gauss(seed, sd):
-    clamp = 0.5
-    if sd <= 0.0:
-        return 1.0
-    while True:
-        x = -6.0
-        for i in range(12):
-            seed = int(0xDEECE66D) * seed + 0xB
-            x += float((seed >> 8) & 0xffffff) / float(1 << 24)
-        x *= sd
-        if abs(x) <= clamp:
-            break
-    return x + 1.0
-
-
-@cuda.jit()
-def wave_kernel(ops, op_start, op_stop, state, sat, st_start, st_stop, line_times, sd, seed):
-    x, y = cuda.grid(2)
-    st_idx = st_start + x
-    op_idx = op_start + y
-    if st_idx >= st_stop: return
-    if op_idx >= op_stop: return
-    lut = ops[op_idx, 0]
-    z_idx = ops[op_idx, 1]
-    a_idx = ops[op_idx, 2]
-    b_idx = ops[op_idx, 3]
-    overflows = int(0)
-
-    _seed = (seed << 4) + (z_idx << 20) + (st_idx << 1)
-
-    a_mem = sat[a_idx, 0]
-    b_mem = sat[b_idx, 0]
-    z_mem, z_cap, _ = sat[z_idx]
-
-    a_cur = int(0)
-    b_cur = int(0)
-    z_cur = lut & 1
-    if z_cur == 1:
-        state[z_mem, st_idx] = TMIN
-
-    a = state[a_mem, st_idx] + line_times[a_idx, 0, z_cur] * rand_gauss(_seed ^ a_mem ^ z_cur, sd)
-    b = state[b_mem, st_idx] + line_times[b_idx, 0, z_cur] * rand_gauss(_seed ^ b_mem ^ z_cur, sd)
-
-    previous_t = TMIN
-
-    current_t = min(a, b)
-    inputs = int(0)
-
-    while current_t < TMAX:
-        z_val = z_cur & 1
-        if b < a:
-            b_cur += 1
-            b = state[b_mem + b_cur, st_idx]
-            b += line_times[b_idx, 0, z_val ^ 1] * rand_gauss(_seed ^ b_mem ^ z_val ^ 1, sd)
-            thresh = line_times[b_idx, 1, z_val] * rand_gauss(_seed ^ b_mem ^ z_val, sd)
-            inputs ^= 2
-            next_t = b
-        else:
-            a_cur += 1
-            a = state[a_mem + a_cur, st_idx]
-            a += line_times[a_idx, 0, z_val ^ 1] * rand_gauss(_seed ^ a_mem ^ z_val ^ 1, sd)
-            thresh = line_times[a_idx, 1, z_val] * rand_gauss(_seed ^ a_mem ^ z_val, sd)
-            inputs ^= 1
-            next_t = a
-
-        if (z_cur & 1) != ((lut >> inputs) & 1):
-            # we generate a toggle in z_mem, if:
-            #   ( it is the first toggle in z_mem OR
-            #   following toggle is earlier OR
-            #   pulse is wide enough ) AND enough space in z_mem.
-            if z_cur == 0 or next_t < current_t or (current_t - previous_t) > thresh:
-                if z_cur < (z_cap - 1):
-                    state[z_mem + z_cur, st_idx] = current_t
-                    previous_t = current_t
-                    z_cur += 1
-                else:
-                    overflows += 1
-                    previous_t = state[z_mem + z_cur - 1, st_idx]
-                    z_cur -= 1
-            else:
-                z_cur -= 1
-                if z_cur > 0:
-                    previous_t = state[z_mem + z_cur - 1, st_idx]
-                else:
-                    previous_t = TMIN
-        current_t = min(a, b)
-        
-    if overflows > 0:
-        state[z_mem + z_cur, st_idx] = TMAX_OVL
-    else:
-        state[z_mem + z_cur, st_idx] = a if a > b else b  # propagate overflow flags by storing biggest TMAX from input

tests/test_bench.py

@@ -5,7 +5,7 @@ def test_b01(mydir):
     with open(mydir / 'b01.bench', 'r') as f:
         c = bench.parse(f.read())
         assert 92 == len(c.nodes)
-    c = bench.parse(mydir / 'b01.bench')
+    c = bench.load(mydir / 'b01.bench')
     assert 92 == len(c.nodes)
 
 

tests/test_logic.py

@@ -23,6 +23,14 @@ def test_mvarray():
     assert ary.length == 1
     assert ary.width == 4
 
+    ary = lg.MVArray("1")
+    assert ary.length == 1
+    assert ary.width == 1
+
+    ary = lg.MVArray(["1"])
+    assert ary.length == 1
+    assert ary.width == 1
+
     # instantiation with multiple vectors
 
     ary = lg.MVArray([[0, 0], [0, 1], [1, 0], [1, 1]])
@@ -53,14 +61,14 @@ def test_mvarray():
 
     # casting to 4-valued logic
 
-    ary = lg.MVArray([0, 1, 2, None, 'F'])
+    ary = lg.MVArray([0, 1, 2, None, 'F'], m=4)
     assert ary.data[0] == lg.ZERO
     assert ary.data[1] == lg.ONE
     assert ary.data[2] == lg.UNKNOWN
     assert ary.data[3] == lg.UNASSIGNED
     assert ary.data[4] == lg.ZERO
 
-    ary = lg.MVArray("0-X1PRFN")
+    ary = lg.MVArray("0-X1PRFN", m=4)
     assert ary.data[0] == lg.ZERO
     assert ary.data[1] == lg.UNASSIGNED
     assert ary.data[2] == lg.UNKNOWN
@@ -77,7 +85,7 @@ def test_mvarray():
     assert ary.data[1] == lg.ONE
     assert ary.data[2] == lg.UNKNOWN
     assert ary.data[3] == lg.UNASSIGNED
-    assert ary.data[4] == lg.FALLING
+    assert ary.data[4] == lg.FALL
 
     ary = lg.MVArray("0-X1PRFN", m=8)
     assert ary.data[0] == lg.ZERO
@@ -85,8 +93,8 @@ def test_mvarray():
     assert ary.data[2] == lg.UNKNOWN
     assert ary.data[3] == lg.ONE
     assert ary.data[4] == lg.PPULSE
-    assert ary.data[5] == lg.RISING
-    assert ary.data[6] == lg.FALLING
+    assert ary.data[5] == lg.RISE
+    assert ary.data[6] == lg.FALL
     assert ary.data[7] == lg.NPULSE
 
     # copy constructor and casting
@@ -103,3 +111,28 @@ def test_mvarray():
     ary2 = lg.MVArray(ary, m=2)
     assert ary2.data[1] == lg.ZERO
     assert ary2.data[7] == lg.ONE
+
+
+def test_mv_operations():
+    x1_2v = lg.MVArray("0011", m=2)
+    x2_2v = lg.MVArray("0101", m=2)
+    x1_4v = lg.MVArray("0000XXXX----1111", m=4)
+    x2_4v = lg.MVArray("0X-10X-10X-10X-1", m=4)
+    x1_8v = lg.MVArray("00000000XXXXXXXX--------11111111PPPPPPPPRRRRRRRRFFFFFFFFNNNNNNNN", m=8)
+    x2_8v = lg.MVArray("0X-1PRFN0X-1PRFN0X-1PRFN0X-1PRFN0X-1PRFN0X-1PRFN0X-1PRFN0X-1PRFN", m=8)
+
+    assert str(lg.mv_not(x1_2v)) == "['1100']"
+    assert str(lg.mv_not(x1_4v)) == "['1111XXXXXXXX0000']"
+    assert str(lg.mv_not(x1_8v)) == "['11111111XXXXXXXXXXXXXXXX00000000NNNNNNNNFFFFFFFFRRRRRRRRPPPPPPPP']"
+
+    assert str(lg.mv_or(x1_2v, x2_2v)) == "['0111']"
+    assert str(lg.mv_or(x1_4v, x2_4v)) == "['0XX1XXX1XXX11111']"
+    assert str(lg.mv_or(x1_8v, x2_8v)) == "['0XX1PRFNXXX1XXXXXXX1XXXX11111111PXX1PRFNRXX1RRNNFXX1FNFNNXX1NNNN']"
+
+    assert str(lg.mv_and(x1_2v, x2_2v)) == "['0001']"
+    assert str(lg.mv_and(x1_4v, x2_4v)) == "['00000XXX0XXX0XX1']"
+    assert str(lg.mv_and(x1_8v, x2_8v)) == "['000000000XXXXXXX0XXXXXXX0XX1PRFN0XXPPPPP0XXRPRPR0XXFPPFF0XXNPRFN']"
+
+    assert str(lg.mv_xor(x1_2v, x2_2v)) == "['0110']"
+    assert str(lg.mv_xor(x1_4v, x2_4v)) == "['0XX1XXXXXXXX1XX0']"
+    assert str(lg.mv_xor(x1_8v, x2_8v)) == "['0XX1PRFNXXXXXXXXXXXXXXXX1XX0NFRPPXXNPRFNRXXFRPNFFXXRFNPRNXXPNFRP']"

tests/test_logic_sim.py

@@ -141,7 +141,7 @@ def test_vd3():
         
 
 def test_b01(mydir):
-    c = bench.parse(mydir / 'b01.bench')
+    c = bench.load(mydir / 'b01.bench')
 
     # 2-valued
     s = LogicSim(c, 8)

tests/test_sdf.py

@@ -74,13 +74,13 @@ def test_parse():
 
 
 def test_b14(mydir):
-    df = sdf.parse(mydir / 'b14.sdf.gz')
+    df = sdf.load(mydir / 'b14.sdf.gz')
     assert df.name == 'b14'
 
 
 def test_gates(mydir):
-    c = verilog.parse(mydir / 'gates.v')
-    df = sdf.parse(mydir / 'gates.sdf')
+    c = verilog.load(mydir / 'gates.v')
+    df = sdf.load(mydir / 'gates.sdf')
     lt = df.annotation(c, pin_index, dataset=1)
     nand_a = c.cells['nandgate'].ins[0]
     nand_b = c.cells['nandgate'].ins[1]

tests/test_stil.py

@@ -2,7 +2,7 @@ from kyupy import stil
 
 
 def test_b14(mydir):
-    s = stil.parse(mydir / 'b14.stuck.stil.gz')
+    s = stil.load(mydir / 'b14.stuck.stil.gz')
     assert 10 == len(s.signal_groups)
     assert 1 == len(s.scan_chains)
     assert 2163 == len(s.calls)

tests/test_verilog.py

@@ -5,5 +5,4 @@ def test_b01(mydir):
     with open(mydir / 'b01.v', 'r') as f:
         modules = verilog.parse(f.read())
     assert modules is not None
-    assert verilog.parse(mydir / 'b01.v') is not None
-
+    assert verilog.load(mydir / 'b01.v') is not None

tests/test_wave_sim.py

@@ -1,11 +1,10 @@
 import numpy as np
-from kyupy.wave_sim import WaveSim, wave_eval, TMIN, TMAX
+from kyupy.wave_sim import WaveSim, WaveSimCuda, wave_eval, TMIN, TMAX
 from kyupy.logic_sim import LogicSim
 from kyupy import verilog
 from kyupy import sdf
 from kyupy.saed import pin_index
 from kyupy.packed_vectors import PackedVectors
-from kyupy.wave_sim_cuda import WaveSimCuda
 
 
 def test_wave_eval():
@@ -122,24 +121,24 @@ def compare_to_logic_sim(wsim):
 
 
 def test_b14(mydir):
-    c = verilog.parse(mydir / 'b14.v.gz', branchforks=True)
-    df = sdf.parse(mydir / 'b14.sdf.gz')
+    c = verilog.load(mydir / 'b14.v.gz', branchforks=True)
+    df = sdf.load(mydir / 'b14.sdf.gz')
     lt = df.annotation(c, pin_index)
     wsim = WaveSim(c, lt, 8)
     compare_to_logic_sim(wsim)
 
 
 def test_b14_strip_forks(mydir):
-    c = verilog.parse(mydir / 'b14.v.gz', branchforks=True)
-    df = sdf.parse(mydir / 'b14.sdf.gz')
+    c = verilog.load(mydir / 'b14.v.gz', branchforks=True)
+    df = sdf.load(mydir / 'b14.sdf.gz')
     lt = df.annotation(c, pin_index)
     wsim = WaveSim(c, lt, 8, strip_forks=True)
     compare_to_logic_sim(wsim)
 
 
 def test_b14_cuda(mydir):
-    c = verilog.parse(mydir / 'b14.v.gz', branchforks=True)
-    df = sdf.parse(mydir / 'b14.sdf.gz')
+    c = verilog.load(mydir / 'b14.v.gz', branchforks=True)
+    df = sdf.load(mydir / 'b14.sdf.gz')
     lt = df.annotation(c, pin_index)
     wsim = WaveSimCuda(c, lt, 8)
     compare_to_logic_sim(wsim)