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CUTLASS 2.2 (#96)

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Adds support for NVIDIA Ampere Architecture features. CUDA 11 Toolkit recommended.
This commit is contained in:
Andrew Kerr
2020-06-08 16:17:35 -07:00
committed by GitHub
parent e33d90b361
commit 86931fef85
584 changed files with 51080 additions and 3373 deletions
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tools/profiler/src/device_allocation.cu
+48 -1
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@@ -1,5 +1,5 @@
/***************************************************************************************************
* Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.
* Copyright (c) 2017-2020, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without modification, are permitted
* provided that the following conditions are met:
@@ -431,6 +431,14 @@ void DeviceAllocation::initialize_random_device(int seed, Distribution dist) {
dist
);
break;
case library::NumericTypeID::kCF32:
cutlass::reference::device::BlockFillRandom<cutlass::complex<float>>(
reinterpret_cast<cutlass::complex<float> *>(pointer_),
capacity_,
seed,
dist
);
break;
case library::NumericTypeID::kF64:
cutlass::reference::device::BlockFillRandom<double>(
reinterpret_cast<double *>(pointer_),
@@ -548,6 +556,14 @@ void DeviceAllocation::initialize_random_host(int seed, Distribution dist) {
dist
);
break;
case library::NumericTypeID::kCF32:
cutlass::reference::host::BlockFillRandom<cutlass::complex<float>>(
reinterpret_cast<cutlass::complex<float> *>(host_data.data()),
capacity_,
seed,
dist
);
break;
case library::NumericTypeID::kF64:
cutlass::reference::host::BlockFillRandom<double>(
reinterpret_cast<double *>(host_data.data()),
@@ -655,6 +671,12 @@ bool DeviceAllocation::block_compare_equal(
reinterpret_cast<float const *>(ptr_A),
reinterpret_cast<float const *>(ptr_B),
capacity);
case library::NumericTypeID::kCF32:
return reference::device::BlockCompareEqual<cutlass::complex<float> >(
reinterpret_cast<complex<float> const *>(ptr_A),
reinterpret_cast<complex<float> const *>(ptr_B),
capacity);
case library::NumericTypeID::kCF16:
return reference::device::BlockCompareEqual<complex<half_t>>(
@@ -825,6 +847,23 @@ bool DeviceAllocation::block_compare_relatively_equal(
static_cast<uint64_t>(epsilon),
static_cast<uint64_t>(nonzero_floor));
// No relatively equal comparison for complex numbers.
//
// As a simplification, we can require bitwise equality. This avoids false positives.
// (i.e. "pass" really means passing. "Fail" may not actually mean failure given appropriate epsilon.)
//
case library::NumericTypeID::kCF32:
return reference::device::BlockCompareEqual<cutlass::complex<float> >(
reinterpret_cast<complex<float> const *>(ptr_A),
reinterpret_cast<complex<float> const *>(ptr_B),
capacity);
case library::NumericTypeID::kCF64:
return reference::device::BlockCompareEqual<cutlass::complex<double> >(
reinterpret_cast<complex<double> const *>(ptr_A),
reinterpret_cast<complex<double> const *>(ptr_B),
capacity);
default:
throw std::runtime_error("Unsupported numeric type");
}
@@ -970,6 +1009,14 @@ void DeviceAllocation::write_tensor_csv(
case library::NumericTypeID::kU64:
write_tensor_csv_static_type<uint64_t>(out, *this);
break;
case library::NumericTypeID::kCF32:
write_tensor_csv_static_type<cutlass::complex<float> >(out, *this);
break;
case library::NumericTypeID::kCF64:
write_tensor_csv_static_type<cutlass::complex<double> >(out, *this);
break;
default:
throw std::runtime_error("Unsupported numeric type");