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Commit 29187952 authored by Akash Kothari's avatar Akash Kothari
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Combine HPVM and ApproxHPVM intrinsics table files

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hpvm/llvm_patches/include/IR/IntrinsicsApproxHPVM.td deleted 100644 → 0
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//===- IntrinsicsHPVM.td - Defines HPVM intrinsics ---------*- tablegen -*-===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// This file defines all of the HPVM-specific intrinsics.
//
//===----------------------------------------------------------------------===//
let TargetPrefix = "hpvm" in {
/* All intrinsics start with "llvm.hpvm."
* As we do not want the compiler to mess with these intrinsics, we assume
* worst memory behavior for all these intrinsics.
*/
/* Initialization intrinsic -
* i8* llvm.hpvm.setup(function*);
*/
def int_hpvm_init : Intrinsic<[], [], []>;
/* Launch intrinsic - with streaming argument
* i8* llvm.hpvm.launch(i8*, ArgList*, i1);
*/
def int_hpvm_launch : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_ptr_ty, llvm_i1_ty], []>;
/* Push intrinsic - push data on streaming pipeline
* void llvm.hpvm.push(i8*, ArgList*);
*/
def int_hpvm_push : Intrinsic<[], [llvm_ptr_ty, llvm_ptr_ty], []>;
/* Pop intrinsic - pop data from streaming pipeline
* i8* llvm.hpvm.pop(i8*);
*/
def int_hpvm_pop : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], []>;
/* Cleanup intrinsic -
* void llvm.hpvm.cleanup(i8*);
*/
def int_hpvm_cleanup : Intrinsic<[], [], []>;
/* Wait intrinsic -
* void llvm.hpvm.wait(graphID*);
*/
def int_hpvm_wait : Intrinsic<[], [llvm_ptr_ty], []>;
/* Track memory intrinsic -
* void llvm.hpvm.trackMemory(i8*, i64);
*/
def int_hpvm_trackMemory : Intrinsic<[], [llvm_ptr_ty, llvm_i64_ty], []>;
/* Track memory intrinsic -
* void llvm.hpvm.untrackMemory(i8*);
*/
def int_hpvm_untrackMemory : Intrinsic<[], [llvm_ptr_ty], []>;
/* Request memory intrinsic -
* void llvm.hpvm.requestMemory(i8*, i64);
*/
def int_hpvm_requestMemory : Intrinsic<[], [llvm_ptr_ty, llvm_i64_ty], []>;
/* Create Node intrinsic -
* i8* llvm.hpvm.createNode(function*);
*/
def int_hpvm_createNode : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], []>;
/* Create Node 1D array intrinsic -
* i8* llvm.hpvm.createNode1D(function*, i64);
*/
def int_hpvm_createNode1D : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_i64_ty], []>;
/* Create Node 2D array intrinsic -
* i8* llvm.hpvm.createNode2D(function*, i64, i64);
*/
def int_hpvm_createNode2D : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_i64_ty, llvm_i64_ty], []>;
/* Create Node 3D array intrinsic -
* i8* llvm.hpvm.createNode2D(function*, i64, i64, i64);
*/
def int_hpvm_createNode3D : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_i64_ty, llvm_i64_ty, llvm_i64_ty],
[]>;
/* Create dataflow edge intrinsic -
* i8* llvm.hpvm.createEdge(i8*, i8*, i1, i32, i32, i1);
*/
def int_hpvm_createEdge : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty, llvm_ptr_ty,
llvm_i1_ty, llvm_i32_ty, llvm_i32_ty,
llvm_i1_ty],
[]>;
/* Create bind input intrinsic -
* void llvm.hpvm.bind.input(i8*, i32, i32);
*/
def int_hpvm_bind_input : Intrinsic<[], [llvm_ptr_ty, llvm_i32_ty,
llvm_i32_ty, llvm_i1_ty], []>;
/* Create bind output intrinsic -
* void llvm.hpvm.bind.output(i8*, i32, i32);
*/
def int_hpvm_bind_output : Intrinsic<[], [llvm_ptr_ty, llvm_i32_ty,
llvm_i32_ty, llvm_i1_ty], []>;
/* Find associated dataflow node intrinsic -
* i8* llvm.hpvm.getNode();
*/
def int_hpvm_getNode : Intrinsic<[llvm_ptr_ty], [], [IntrNoMem]>;
/* Find parent dataflow node intrinsic -
* i8* llvm.hpvm.getParentNode(i8*);
*/
def int_hpvm_getParentNode : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], [IntrNoMem]>;
/* Find the number of dimensions of a dataflow node intrinsic -
* i32 llvm.hpvm.getNumDims(i8*);
*/
def int_hpvm_getNumDims : Intrinsic<[llvm_i32_ty], [llvm_ptr_ty], [IntrNoMem]>;
/* Find the unique indentifier of a dataflow node (with respect to his parent
* node) in the specified dimension intrinsic -
*/
/* i64 llvm.hpvm.getNodeInstanceID.[xyz](i8*);
*/
def int_hpvm_getNodeInstanceID_x : Intrinsic<[llvm_i64_ty], [llvm_ptr_ty],
[IntrNoMem]>;
def int_hpvm_getNodeInstanceID_y : Intrinsic<[llvm_i64_ty], [llvm_ptr_ty],
[IntrNoMem]>;
def int_hpvm_getNodeInstanceID_z : Intrinsic<[llvm_i64_ty], [llvm_ptr_ty],
[IntrNoMem]>;
/* Find the number of instances of a dataflow node in the specified dimension
* intrinsic -
*/
/* i64 llvm.hpvm.getNumNodeInstances.[xyz](i8*);
*/
def int_hpvm_getNumNodeInstances_x : Intrinsic<[llvm_i64_ty], [llvm_ptr_ty],
[IntrNoMem]>;
def int_hpvm_getNumNodeInstances_y : Intrinsic<[llvm_i64_ty], [llvm_ptr_ty],
[IntrNoMem]>;
def int_hpvm_getNumNodeInstances_z : Intrinsic<[llvm_i64_ty], [llvm_ptr_ty],
[IntrNoMem]>;
/* Local Barrier
* void llvm.hpvm.barrier();
*/
def int_hpvm_barrier : Intrinsic<[], [], []>;
/* Memory allocation inside the graph
* i8* llvm.hpvm.malloc();
*/
def int_hpvm_malloc : Intrinsic<[llvm_ptr_ty], [llvm_i64_ty], []>;
/* Find the vector length supported by target architecture
* intrinsic -
* i32 llvm.hpvm.getVectorLength();
*/
def int_hpvm_getVectorLength : Intrinsic<[llvm_i32_ty], [], []>;
/* ============ Atomic intrinsics ============= */
// Atomic arithmetic operations
/* i32 llvm.hpvm.atomic.add(i32*, i32)*/
def int_hpvm_atomic_add: Intrinsic<[llvm_i32_ty], [llvm_ptr_ty, llvm_i32_ty],
[]>;
/* i32 llvm.hpvm.atomic.sub(i32*, i32)*/
def int_hpvm_atomic_sub: Intrinsic<[llvm_i32_ty], [llvm_ptr_ty, llvm_i32_ty],
[]>;
/* i32 llvm.hpvm.atomic.xchg(i32*, i32)*/
def int_hpvm_atomic_xchg: Intrinsic<[llvm_i32_ty], [llvm_ptr_ty, llvm_i32_ty],
[]>;
/* i32 llvm.hpvm.atomic.min(i32*, i32)*/
def int_hpvm_atomic_min: Intrinsic<[llvm_i32_ty], [llvm_ptr_ty, llvm_i32_ty],
[]>;
/* i32 llvm.hpvm.atomic.maxi32*, i32)*/
def int_hpvm_atomic_max: Intrinsic<[llvm_i32_ty], [llvm_ptr_ty, llvm_i32_ty],
[]>;
// Atomic bitwise operations
/* i32 llvm.hpvm.atomic.and(i32*, i32)*/
def int_hpvm_atomic_and: Intrinsic<[llvm_i32_ty], [llvm_ptr_ty, llvm_i32_ty],
[]>;
/* i32 llvm.hpvm.atomic.or(i32*, i32)*/
def int_hpvm_atomic_or: Intrinsic<[llvm_i32_ty], [llvm_ptr_ty, llvm_i32_ty],
[]>;
/* i32 llvm.hpvm.atomic.xor(i32*, i32)*/
def int_hpvm_atomic_xor: Intrinsic<[llvm_i32_ty], [llvm_ptr_ty, llvm_i32_ty],
[]>;
/***************************************************************************/
/* ApproxHPVM intrinsics */
/***************************************************************************/
/* Tensor add intrinsic
* i8* llvm.hpvm.tensor.add(i8*, i8*);
*/
def int_hpvm_tensor_add : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_ptr_ty], []>;
/* Tensor mul intrinsic
* i8* llvm.hpvm.tensor.mul(i8*, i8*);
*/
def int_hpvm_tensor_mul : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_ptr_ty], []>;
/* Tensor relu intrinsic
* i8* llvm.hpvm.tensor.relu(i8*);
*/
def int_hpvm_tensor_relu : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], []>;
/* Tensor clipped relu intrinsic
* i8* llvm.hpvm.tensor.clipped.relu(i8*);
*/
def int_hpvm_tensor_clipped_relu : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], []>;
/* Tensor tanh intrinsic
* i8* llvm.hpvm.tensor.tanh(i8*);
*/
def int_hpvm_tensor_tanh : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], []>;
/* Tensor sigmoid intrinsic
* i8* llvm.hpvm.tensor.sigmoid(i8*);
*/
def int_hpvm_tensor_sigmoid : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], []>;
/* Tensor softmax intrinsic
* i8* llvm.hpvm.tensor.softmax(i8*);
*/
def int_hpvm_tensor_softmax : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], []>;
/* Tensor convolution intrinsic
* i8* llvm.hpvm.tensor.convolution(i8*, i8*, i32, i32, i32, i32);
*/
def int_hpvm_tensor_convolution : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_ptr_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty], []>;
/* Tensor group convolution intrinsic
* i8* llvm.hpvm.tensor.group.convolution(i8*, i8*, i32, i32, i32, i32, i32, i32);
*/
def int_hpvm_tensor_group_convolution : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_ptr_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty], []>;
/* Tensor BatchNorm intrinsic
* i8* llvm.hpvm.tensor.batchnorm(i8*, i8*, i8*, i8*, i8*, double);
*/
def int_hpvm_tensor_batchnorm : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_ptr_ty,
llvm_ptr_ty,
llvm_ptr_ty,
llvm_ptr_ty,
llvm_double_ty], []>;
/* Tensor pool intrinsics: max, min, average
* i8* llvm.hpvm.tensor.pool.max(i8*, i32, i32, i32, i32, i32, i32);
* i8* llvm.hpvm.tensor.pool.min(i8*, i32, i32, i32, i32, i32, i32);
* i8* llvm.hpvm.tensor.pool.average(i8*, i32, i32, i32, i32, i32, i32);
*/
def int_hpvm_tensor_pool_max : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty], []>;
def int_hpvm_tensor_pool_min : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty], []>;
def int_hpvm_tensor_pool_mean : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty], []>;
def int_hpvm_node_id : Intrinsic<[llvm_ptr_ty], [llvm_i32_ty], []>;
}
hpvm/llvm_patches/include/IR/IntrinsicsHPVM.td
+ 103
− 0
View file @ 29187952
...@@ -205,4 +205,107 @@ let TargetPrefix = "hpvm" in { ...@@ -205,4 +205,107 @@ let TargetPrefix = "hpvm" in {
def int_hpvm_atomic_xor: Intrinsic<[llvm_i32_ty], [llvm_ptr_ty, llvm_i32_ty], def int_hpvm_atomic_xor: Intrinsic<[llvm_i32_ty], [llvm_ptr_ty, llvm_i32_ty],
[]>; []>;
/***************************************************************************/
/* ApproxHPVM intrinsics */
/***************************************************************************/
/* Tensor add intrinsic
* i8* llvm.hpvm.tensor.add(i8*, i8*);
*/
def int_hpvm_tensor_add : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_ptr_ty], []>;
/* Tensor mul intrinsic
* i8* llvm.hpvm.tensor.mul(i8*, i8*);
*/
def int_hpvm_tensor_mul : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_ptr_ty], []>;
/* Tensor relu intrinsic
* i8* llvm.hpvm.tensor.relu(i8*);
*/
def int_hpvm_tensor_relu : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], []>;
/* Tensor clipped relu intrinsic
* i8* llvm.hpvm.tensor.clipped.relu(i8*);
*/
def int_hpvm_tensor_clipped_relu : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], []>;
/* Tensor tanh intrinsic
* i8* llvm.hpvm.tensor.tanh(i8*);
*/
def int_hpvm_tensor_tanh : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], []>;
/* Tensor sigmoid intrinsic
* i8* llvm.hpvm.tensor.sigmoid(i8*);
*/
def int_hpvm_tensor_sigmoid : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], []>;
/* Tensor softmax intrinsic
* i8* llvm.hpvm.tensor.softmax(i8*);
*/
def int_hpvm_tensor_softmax : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty], []>;
/* Tensor convolution intrinsic
* i8* llvm.hpvm.tensor.convolution(i8*, i8*, i32, i32, i32, i32);
*/
def int_hpvm_tensor_convolution : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_ptr_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty], []>;
/* Tensor group convolution intrinsic
* i8* llvm.hpvm.tensor.group.convolution(i8*, i8*, i32, i32, i32, i32, i32, i32);
*/
def int_hpvm_tensor_group_convolution : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_ptr_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty], []>;
/* Tensor BatchNorm intrinsic
* i8* llvm.hpvm.tensor.batchnorm(i8*, i8*, i8*, i8*, i8*, double);
*/
def int_hpvm_tensor_batchnorm : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_ptr_ty,
llvm_ptr_ty,
llvm_ptr_ty,
llvm_ptr_ty,
llvm_double_ty], []>;
/* Tensor pool intrinsics: max, min, average
* i8* llvm.hpvm.tensor.pool.max(i8*, i32, i32, i32, i32, i32, i32);
* i8* llvm.hpvm.tensor.pool.min(i8*, i32, i32, i32, i32, i32, i32);
* i8* llvm.hpvm.tensor.pool.average(i8*, i32, i32, i32, i32, i32, i32);
*/
def int_hpvm_tensor_pool_max : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty], []>;
def int_hpvm_tensor_pool_min : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty], []>;
def int_hpvm_tensor_pool_mean : Intrinsic<[llvm_ptr_ty], [llvm_ptr_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty,
llvm_i32_ty], []>;
def int_hpvm_node_id : Intrinsic<[llvm_ptr_ty], [llvm_i32_ty], []>;
} }
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