[vector] RFR (L): Generalized intrinsics for vector operations (first batch)

[Vladimir Ivanov]

After thinking about it a bit more, I decided to keep casts & intrinsic 
calls separate:
 
http://cr.openjdk.java.net/~vlivanov/panama/vector.generalized_intrinsics/webrev.06.cast/

Also, added missing null checks on Mask-related operations.

Let me know what do you think about new shape.

Best regards,
Vladimir Ivanov

On 2/10/18 1:42 AM, Paul Sandoz wrote:
> 
> 
>> On Feb 9, 2018, at 2:24 PM, Vladimir Ivanov <vladimir.x.ivanov at oracle.com> wrote:
>>
>> Thanks, Paul.
>>
>> On 2/10/18 1:14 AM, Paul Sandoz wrote:
>>> Looks good.
>>>   139     @Override
>>>   140     @ForceInline
>>>   141     public $vectortype$ add(Vector<$Boxtype$,Shapes.$shape$> v) {
>>>   142         Objects.requireNonNull(v);
>>>   143         return ($vectortype$) VectorIntrinsics.binaryOp(
>>>   144             VECTOR_OP_ADD, $vectortype$.class, $type$.class, LENGTH,
>>>   145             this, ($vectortype$)v,
>>>   146             (v1, v2) -> (($vectortype$)v1).bOp(v2, (i, a, b) -> ($type$)(a + b)));
>>>   147     }
>>> Given you perform the cast at line 145, so both input vectors are of the same concrete type, do you require it on v1 in the lambda?
>>
>> Good point. It can be even further simplified to:
>>
>>     public Int256Vector add(Vector<Integer,Shapes.S256Bit> v) {
>>         Objects.requireNonNull(v);
>>         return VectorIntrinsics.binaryOp(
>>             VECTOR_OP_ADD, Int256Vector.class, int.class, LENGTH,
>>             this, v,
>>             (v1, v2) -> v1.bOp(v2, (i, a, b) -> (int)(a + b)));
>>     }
>>
> 
> Right, i thought you might want the explicit cast for reasons you say, so i am ok with it.
> 
> Paul.
>   
>> But I'd prefer to keep the cast at line 145 explicit to stress there's a type check in place on the argument.
>>
>> I'll use the following shape:
>>
>> 139     @Override
>> 140     @ForceInline
>> 141     public $vectortype$ add(Vector<$Boxtype$,Shapes.$shape$> v) {
>> 142         Objects.requireNonNull(v);
>> 143         return VectorIntrinsics.binaryOp(
>> 144             VECTOR_OP_ADD, $vectortype$.class, $type$.class, LENGTH,
>> 145             this, ($vectortype$)v,
>> 146             (v1, v2) -> v1.bOp(v2, (i, a, b) -> ($type$)(a + b)));
>> 147     }
>>
>> Are you ok with it?
>>
>> Best regards,
>> Vladimir Ivanov
>>
>>> Paul.
>>>> On Feb 9, 2018, at 1:38 PM, Vladimir Ivanov <vladimir.x.ivanov at oracle.com> wrote:
>>>>
>>>> http://cr.openjdk.java.net/~vlivanov/panama/vector.generalized_intrinsics/webrev.06/
>>>>
>>>> Here's the first batch of rewritten intrinsics for vector operations.
>>>>
>>>> Main motivation for new implementation is:
>>>>   * reduce number of intrinsic needed;
>>>>   * improve intrinsification robustness;
>>>>   * minimize changes needed in shared C2 code.
>>>>
>>>> The idea of generalized intrinsics is to parameterize them with additional information (passed as constant arguments), so JIT-compiler has enough information to dispatch to proper implementation during intrinsification.
>>>>
>>>> For example, binary vector operation can be represented as:
>>>>
>>>>   // (V,V) -> V
>>>>   @HotSpotIntrinsicCandidate
>>>>   static <V> V binaryOp(int oprId, Class<V> vectorClass,
>>>>                         Class<?> elementType, int vlen,
>>>>                         V v1, V v2,
>>>>                         BiFunction<V,V,V> defaultImpl) {
>>>>       return defaultImpl.apply(v1, v2);
>>>>   }
>>>>
>>>> and used as:
>>>>
>>>>   // (Int256Vector,Int256Vector) -> Int256Vector
>>>>
>>>>   public Int256Vector add(Vector<Integer,Shapes.S256Bit> v) {
>>>>     return (Int256Vector) VectorIntrinsics.binaryOp(
>>>>             VECTOR_OP_ADD,
>>>>             Int256Vector.class, int.class, 8,
>>>>             this, (Int256Vector)v,
>>>>             (v1, v2) -> ((Int256Vector)v1).bOp(v2,
>>>>                                    (i, a, b) -> (int)(a+b)));
>>>>   }
>>>>
>>>> where:
>>>>   oprId encodes actual operation (VECTOR_OP_ADD);
>>>>
>>>>   vectorClass, elementType, vlen describe concrete vector class (Int256Vector);
>>>>
>>>>   v1, v2 are actual arguments of vector binary operations;
>>>>
>>>>   defaultImpl - scalar implementation which is used when intrinsification fails.
>>>>
>>>>
>>>> Generalized intrinsics are declared on jdk.incubator.vector.VectorIntrinsics and the patch contains 6 of them:
>>>>   * broadcastCoerced
>>>>   * reductionCoerced
>>>>   * binaryOp
>>>>   * load/store
>>>>   * test
>>>>
>>>> The following vector operations were ported to new mechanism:
>>>>   * broadcast: zero, broadcast, trueMask, falseMask
>>>>   * reduction: addAll, mulAll
>>>>   * binaryOp: add, sub, mul, div, and, or, xor
>>>>   * load/store: intoArray, fromArray
>>>>   * test: anyTrue, allTrue
>>>>
>>>> There's new flag added to turn new intrinsics on/off:
>>>>
>>>> +  product(bool, UseVectorApiGeneralizedIntrinsics, true,
>>>>
>>>> Previous discussions [1] [2].
>>>>
>>>> The patch adds alternative implementations, but doesn't remove existing ones, since there are some code dependencies on them. Once the dependencies are broken, the code will go away.
>>>>
>>>> Thanks!
>>>>
>>>> Best regards,
>>>> Vladimir Ivanov
>>>>
>>>> [1] http://mail.openjdk.java.net/pipermail/panama-dev/2017-November/000748.html
>>>>
>>>> [2] http://mail.openjdk.java.net/pipermail/panama-dev/2017-December/000884.html
>