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Core: Added double-precision tuning, tests and benchmarks

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This commit is contained in:
Philippe Tillet
2016-11-20 22:36:08 -05:00
parent 1f03389be0
commit 54b5b7523d
15 changed files with 184519 additions and 106392 deletions
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167
bench/blas.cpp
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@@ -22,6 +22,42 @@ typedef sc::int_t int_t;
Timer tmr;
/* C++ wrapper for BLAS */
#ifdef BENCH_CLBLAS
template<typename... Args> void clblasAxpy(float, Args... args){ clblasSaxpy(args...); }
template<typename... Args> void clblasAxpy(double, Args... args){ clblasDaxpy(args...); }
template<typename... Args> void clblasDot(float, Args... args){ clblasSdot(args...); }
template<typename... Args> void clblasDot(double, Args... args){ clblasDdot(args...); }
template<typename... Args> void clblasGemv(float, Args... args){ clblasSgemv(args...); }
template<typename... Args> void clblasGemv(double, Args... args){ clblasDgemv(args...); }
template<typename... Args> void clblasGemm(float, Args... args){ clblasSgemm(args...); }
template<typename... Args> void clblasGemm(double, Args... args){ clblasDgemm(args...); }
#endif
#ifdef BENCH_CBLAS
template<typename... Args> void cblasAxpy(float, Args... args){ cblas_saxpy(args...); }
template<typename... Args> void cblasAxpy(double, Args... args){ cblas_daxpy(args...); }
template<typename... Args> void cblasDot(float, Args... args){ cblas_sdot(args...); }
template<typename... Args> void cblasDot(double, Args... args){ cblas_ddot(args...); }
template<typename... Args> void cblasGemv(float, Args... args){ cblas_sgemv(args...); }
template<typename... Args> void cblasGemv(double, Args... args){ cblas_dgemv(args...); }
template<typename... Args> void cblasGemm(float, Args... args){ cblas_sgemm(args...); }
template<typename... Args> void cblasGemm(double, Args... args){ cblas_dgemm(args...); }
#endif
//cuBLAS
#ifdef BENCH_CUBLAS
template<typename... Args> void cublasAxpy(float, Args... args){ cublasSaxpy(args...); }
template<typename... Args> void cublasAxpy(double, Args... args){ cublasDaxpy(args...); }
template<typename... Args> void cublasDot(float, Args... args){ cublasSdot(args...); }
template<typename... Args> void cublasDot(double, Args... args){ cublasDdot(args...); }
template<typename... Args> void cublasGemv(float, Args... args){ cublasSgemv(args...); }
template<typename... Args> void cublasGemv(double, Args... args){ cublasDgemv(args...); }
template<typename... Args> void cublasGemm(float, Args... args){ cublasSgemm(args...); }
template<typename... Args> void cublasGemm(double, Args... args){ cublasDgemm(args...); }
#endif
//
template<class OP, class SYNC>
double bench(OP const & op, SYNC const & sync)
{
@@ -51,6 +87,10 @@ void bench(sc::numeric_type dtype, std::string operation)
#ifdef BENCH_CUBLAS
auto cusync = [&](){ cudaDeviceSynchronize(); };
#endif
bool on_cl = queue.backend()==sc::driver::OPENCL;
bool on_cu = queue.backend()==sc::driver::CUDA;
/*---------*/
/*--BLAS1--*/
/*---------*/
@@ -65,17 +105,18 @@ void bench(sc::numeric_type dtype, std::string operation)
//Bench
times.push_back(bench([&](){y = x + alpha*y;}, sync));
#ifdef BENCH_CLBLAS
if(x.context().backend()==sc::driver::OPENCL)
times.push_back(bench([&]() {clblasSaxpy(N, alpha, cl(x), 0, 1, cl(y), 0, 1, 1, &cl(queue), 0, NULL, NULL);}, sync));
if(on_cl)
times.push_back(bench([&]() {clblasAxpy(T(), N, alpha, cl(x), 0, 1, cl(y), 0, 1, 1, &cl(queue), 0, nullptr, nullptr);}, sync));
#endif
#ifdef BENCH_CBLAS
std::vector<float> cx(N), cy(N);
sc::copy(x, cx);
sc::copy(y, cy);
times.push_back(bench([&](){cblas_saxpy(N, alpha, cx.data(), 1, cy.data(), 1);}, sync));
times.push_back(bench([&](){cblasAxpy(T(), N, alpha, cx.data(), 1, cy.data(), 1);}, sync));
#endif
#ifdef BENCH_CUBLAS
times.push_back(bench([&](){cublasSaxpy(N, alpha, (T*)cu(x), 1, (T*)cu(y), 1);}, cusync));
if(on_cu)
times.push_back(bench([&](){cublasAxpy(T(), N, alpha, (T*)cu(x), 1, (T*)cu(y), 1);}, cusync));
#endif
}
}
@@ -91,17 +132,18 @@ void bench(sc::numeric_type dtype, std::string operation)
//Bench
times.push_back(bench([&](){s = dot(x,y);}, sync));
#ifdef BENCH_CLBLAS
if(x.context().backend()==sc::driver::OPENCL)
times.push_back(bench([&]() {clblasSdot(N, cl(s), 0, cl(x), 0, 1, cl(y), 0, 1, cl(scratch), 1, &cl(queue), 0, NULL, NULL);}, sync));
if(on_cl)
times.push_back(bench([&]() {clblasDot(T(), N, cl(s), 0, cl(x), 0, 1, cl(y), 0, 1, cl(scratch), 1, &cl(queue), 0, nullptr, nullptr);}, sync));
#endif
#ifdef BENCH_CBLAS
std::vector<float> cx(N), cy(N);
sc::copy(x, cx);
sc::copy(y, cy);
times.push_back(bench([&](){cblas_sdot(N, cx.data(), 1, cy.data(), 1);}, sync));
times.push_back(bench([&](){cblasDot(T(), N, cx.data(), 1, cy.data(), 1);}, sync));
#endif
#ifdef BENCH_CUBLAS
times.push_back(bench([&](){cublasSdot(N, (T*)cu(x), 1, (T*)cu(y), 1);}, cusync));
if(on_cu)
times.push_back(bench([&](){cublasDot(T(), N, (T*)cu(x), 1, (T*)cu(y), 1);}, cusync));
#endif
}
}
@@ -146,18 +188,19 @@ void bench(sc::numeric_type dtype, std::string operation)
//Bench
times.push_back(bench([&](){y = AT?dot(A.T,x):dot(A,x);}, sync));
#ifdef BENCH_CLBLAS
if(x.context().backend()==sc::driver::OPENCL)
times.push_back(bench([&]() {clblasSgemv(clblasColumnMajor, AT?clblasTrans:clblasNoTrans, As1, As2, 1, cl(A), 0, lda, cl(x), 0, 1, 0, cl(y), 0, 1, 1, &cl(queue),0, NULL, NULL);}, sync));
if(on_cl)
times.push_back(bench([&]() {clblasGemv(T(), clblasColumnMajor, AT?clblasTrans:clblasNoTrans, As1, As2, 1, cl(A), 0, lda, cl(x), 0, 1, 0, cl(y), 0, 1, 1, &cl(queue),0, nullptr, nullptr);}, sync));
#endif
#ifdef BENCH_CBLAS
std::vector<float> cA(M*N), cx(N), cy(M);
sc::copy(x, cx);
sc::copy(y, cy);
sc::copy(A, cA);
times.push_back(bench([&](){cblas_sgemv(CblasColMajor, AT?CblasTrans:CblasNoTrans, As1, As2, 1, cA.data(), lda, cx.data(), 1, 0, cy.data(), 1);}, sync));
times.push_back(bench([&](){cblasGemv(T(), CblasColMajor, AT?CblasTrans:CblasNoTrans, As1, As2, 1, cA.data(), lda, cx.data(), 1, 0, cy.data(), 1);}, sync));
#endif
#ifdef BENCH_CUBLAS
times.push_back(bench([&](){cublasSgemv(AT?'t':'n', As1, As2, 1, (T*)cu(A), lda, (T*)cu(x), 1, 0, (T*)cu(y), 1);}, cusync));
if(on_cu)
times.push_back(bench([&](){cublasGemv(T(), AT?'t':'n', As1, As2, 1, (T*)cu(A), lda, (T*)cu(x), 1, 0, (T*)cu(y), 1);}, cusync));
#endif
}
}
@@ -185,12 +228,14 @@ void bench(sc::numeric_type dtype, std::string operation)
std::cout << color_stream(ITALIC) << color_stream(BOLD) ;
std::cout << "BENCH\tM\tN\tK\tAT\tBT\tISAAC";
#ifdef BENCH_CLBLAS
if(on_cl)
std::cout << "\tclBLAS";
#endif
#ifdef BENCH_CBLAS
std::cout << "\tBLAS";
#endif
#ifdef BENCH_CUBLAS
if(on_cu)
std::cout << "\tcuBLAS";
#endif
std::cout << color_stream(RESET) << std::endl;
@@ -224,20 +269,21 @@ void bench(sc::numeric_type dtype, std::string operation)
:(BT?dot(A,B.T)
:dot(A,B));}, sync));
#ifdef BENCH_CLBLAS
if(C.context().backend()==sc::driver::OPENCL)
times.push_back(bench([&]() {clblasSgemm(clblasColumnMajor, AT?clblasTrans:clblasNoTrans, BT?clblasTrans:clblasNoTrans,
if(on_cl)
times.push_back(bench([&]() {clblasGemm(T(), clblasColumnMajor, AT?clblasTrans:clblasNoTrans, BT?clblasTrans:clblasNoTrans,
M, N, K, 1, cl(A), 0, lda, cl(B), 0, ldb,
0, cl(C), 0, ldc, 1, &cl(queue),0, NULL, NULL);}, sync));
0, cl(C), 0, ldc, 1, &cl(queue),0, nullptr, nullptr);}, sync));
#endif
#ifdef BENCH_CBLAS
std::vector<float> cC(M*N), cA(M*K), cB(N*K);
sc::copy(C, cC);
sc::copy(A, cA);
sc::copy(B, cB);
times.push_back(bench([&](){cblas_sgemm(CblasColMajor, AT?CblasTrans:CblasNoTrans, BT?CblasTrans:CblasNoTrans, M, N, K, 1, cA.data(), lda, cB.data(), ldb, 1, cC.data(), ldc);}, sync));
times.push_back(bench([&](){cblasGemm(T(), CblasColMajor, AT?CblasTrans:CblasNoTrans, BT?CblasTrans:CblasNoTrans, M, N, K, 1, cA.data(), lda, cB.data(), ldb, 1, cC.data(), ldc);}, sync));
#endif
#ifdef BENCH_CUBLAS
times.push_back(bench([&](){cublasSgemm(AT?'t':'n', BT?'t':'n', M, N, K, 1, (T*)cu(A), lda, (T*)cu(B), ldb, 1, (T*)cu(C), ldc);}, cusync));
if(on_cu)
times.push_back(bench([&](){cublasGemm(T(), AT?'t':'n', BT?'t':'n', M, N, K, 1, (T*)cu(A), lda, (T*)cu(B), ldb, 1, (T*)cu(C), ldc);}, cusync));
#endif
std::transform(times.begin(), times.end(), std::back_inserter(tflops), [&](double t){ return 2*M*N*K/t*1e-3;});
auto fastest = tflops;
@@ -256,6 +302,34 @@ void bench(sc::numeric_type dtype, std::string operation)
}
void handle_misusage(){
std::cerr << "Usage : blas-bench [--dtype {float32, float64}] [--device DEVICE_IDX] [--help]" << std::endl;
// std::cerr << "--op: operation to benchmark" << std::endl;
std::cerr << "--dtype: data-type to benchmark" << std::endl;
std::cerr << "--device: index of isaac device in [0, ..., ndevices - 1]" << std::endl;
std::cerr << "--help: display this message" << std::endl;
exit(EXIT_FAILURE);
}
std::string getopt(std::vector<std::string> const & args,
std::string const & key,
std::vector<std::string> const & set = {},
std::string dft = "")
{
auto it = std::find(args.begin(), args.end(), key);
if(it==args.end()){
if(dft.empty())
handle_misusage();
return dft;
}
auto next = it + 1;
if(next==args.end() || next->compare(0, 2, "--")==0)
handle_misusage();
if(set.size() && std::find(set.begin(), set.end(), *next)==set.end())
handle_misusage();
return *next;
}
int main(int argc, char* argv[])
{
std::vector<std::string> args(argv, argv + argc);
@@ -264,41 +338,38 @@ int main(int argc, char* argv[])
#endif
sc::driver::backend::default_queue_properties = CL_QUEUE_PROFILING_ENABLE;
int device_idx = 0;
std::list<sc::driver::Context const *> contexts;
sc::driver::backend::contexts::get(contexts);
if(std::find(args.begin(), args.end(), "--help") != args.end())
handle_misusage();
std::string operation;
if(contexts.size() > 1)
{
if(args.size() != 3)
{
std::cerr << "usage : blas-bench DEVICE_IDX OPERATION" << std::endl;
std::cout << "Devices available: " << std::endl;
unsigned int current=0;
for(sc::driver::Context const * context: contexts)
{
sc::driver::Device device = sc::driver::backend::queues::get(*context,0).device();
std::cout << current++ << ": " << device.name() << " on " << device.platform().name() << " " << device.platform().version() << std::endl;
}
exit(EXIT_FAILURE);
}
device_idx = atoi(argv[1]);
operation = args[2];
}
else
{
if(args.size() != 2)
{
std::cerr << "usage : blas-bench OPERATION" << std::endl;
exit(EXIT_FAILURE);
}
operation = args[1];
}
std::string operation = "gemm";
std::string dtype = getopt(args, "--dtype", {"float32", "float64"}, "float32");
int device;
try{
device = std::stoi(getopt(args, "--device", {}, "0"));
}catch(...){ handle_misusage(); }
sc::driver::backend::default_device = device;
/* List devices */
std::cout << "Devices available:" << std::endl;
std::cout << "------------------" << std::endl;
size_t i = 0;
std::vector<sc::driver::Platform> platforms;
sc::driver::backend::platforms(platforms);
for(sc::driver::Platform const & pf: platforms){
std::vector<sc::driver::Device> devices;
pf.devices(devices);
for(sc::driver::Device const & device: devices)
std::cout << "[" << (i++==sc::driver::backend::default_device?"x":" ") << "]"
<< " - " << device.name()
<< " on " << pf.name() << std::endl;
}
std::cout << "------------------" << std::endl;
sc::driver::backend::default_device = device_idx;
std::cout << std::fixed << std::setprecision(2);
if(dtype=="float32")
bench<float>(sc::FLOAT_TYPE, operation);
else
bench<double>(sc::DOUBLE_TYPE, operation);
#ifdef BENCH_CLBLAS
clblasTeardown();

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build/bench/bench-blas Executable file
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2
include/isaac/jit/syntax/expression/expression.h
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@@ -134,7 +134,7 @@ public:
data_type const & data() const;
std::size_t root() const;
driver::Context const & context() const;
numeric_type const & dtype() const;
numeric_type dtype() const;
node const & operator[](size_t) const;
node & operator[](size_t);

2
lib/jit/syntax/expression/expression.cpp
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@@ -116,7 +116,7 @@ std::size_t expression_tree::root() const
driver::Context const & expression_tree::context() const
{ return *context_; }
numeric_type const & expression_tree::dtype() const
numeric_type expression_tree::dtype() const
{ return tree_[root_].dtype; }
tuple expression_tree::shape() const

2
lib/runtime/database.cpp
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@@ -48,7 +48,7 @@ namespace runtime
const profiles::presets_type profiles::presets_ =
{
//DEFAULT
DATABASE_ENTRY(UNKNOWN, UNKNOWN, UNKNOWN, database::unknown::unknown),
DATABASE_ENTRY(UNKNOWN, UNKNOWN, UNKNOWN, database::nvidia::sm_6_1),
//INTEL
DATABASE_ENTRY(GPU, INTEL, BROADWELL, database::intel::broadwell),
//NVIDIA

147428
lib/runtime/database/amd/gcn_3.hpp
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2
lib/runtime/database/amd/json/gcn_3.json
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2
lib/runtime/database/nvidia/json/sm_6_1.json
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143220
lib/runtime/database/nvidia/sm_6_1.hpp
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19
lib/runtime/profiles.cpp
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@@ -87,11 +87,11 @@ void profiles::value_type::execute(runtime::execution_handler const & expr)
//Cached
size_t label = 0;
auto it = labels_.find(x);
if(it!=labels_.end()){
if(it!=labels_.end())
label = it->second;
}
//Not cached
else if(predictor_){
else if(predictor_)
{
expression_tree::node const & root = tree[tree.root()];
expression_tree::node const & left = tree[root.binary_operator.lhs];
array_base* out = left.array.base;
@@ -100,12 +100,14 @@ void profiles::value_type::execute(runtime::execution_handler const & expr)
};
bool modify_output = std::find_if(tree.data().begin(), tree.data().end(), read_out) != tree.data().end();
std::unique_ptr<array> bkp;
if(modify_output)
bkp.reset(new array(*out));
if(modify_output){
bkp.reset(new array(out->shape(), out->dtype(), queue_.context()));
*bkp = execution_handler(-(-*out), execution_options_type(queue_));
}
tools::Timer tmr;
std::vector<double> times;
std::vector<float> perf = predictor_->predict(x);
std::vector<size_t> idx(templates_.size());
std::vector<size_t> idx(perf.size());
std::iota(idx.begin(), idx.end(), 0);
std::sort(idx.begin(), idx.end(), [&perf](size_t i1, size_t i2) {return perf[i1] > perf[i2];});
bool valid_found = false;
@@ -133,10 +135,9 @@ void profiles::value_type::execute(runtime::execution_handler const & expr)
}
label = idx[std::distance(times.begin(),std::min_element(times.begin(), times.end()))];
if(modify_output)
*out = *bkp;
}
*out = execution_handler(-(-*bkp), execution_options_type(queue_));
labels_.insert({x, label});
//Executes
}
if(templates_[label]->temporary_workspace(expr.x()) > MAX_TEMPORARY_WORKSPACE)
throw operation_not_supported_exception("Running this operation would require an overly large temporary.");
templates_[label]->enqueue(queue_, program, tools::to_string(label), expr);

1
python/src/bind/core.cpp
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@@ -309,6 +309,7 @@ void export_core()
ADD_ARRAY_OPERATOR(==)
ADD_ARRAY_OPERATOR(!=)
.add_property("context", bp::make_function(&sc::expression_tree::context, bp::return_internal_reference<>()))
.add_property("dtype", &sc::expression_tree::dtype)
.def(bp::self_ns::abs(bp::self))
// .def(bp::self_ns::pow(bp::self))
;

6
tests/common/api.hpp
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@@ -261,7 +261,7 @@ bool diff(isaac::array const & x, VecType const & y, typename VecType::value_typ
{START1, START1 + STRIDE1*SUBM, STRIDE1}));\
template<typename test_fun_t>
int run_test(test_fun_t const & testf, test_fun_t const & /*testd*/)
int run_test(test_fun_t const & testf, test_fun_t const & testd)
{
int nfail = 0;
int npass = 0;
@@ -275,8 +275,8 @@ int run_test(test_fun_t const & testf, test_fun_t const & /*testd*/)
std::cout << "Device: " << device.name() << " on " << device.platform().name() << " " << device.platform().version() << std::endl;
std::cout << "---" << std::endl;
testf(*context, nfail, npass);
// if(device.fp64_support())
// testd(*context, nfail, npass);
if(device.fp64_support())
testd(*context, nfail, npass);
std::cout << "---" << std::endl;
}
if(nfail>0)

28
tune/android/tune/tools.py
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@@ -23,6 +23,8 @@ from math import ceil, exp, log, sqrt
import time
profile_execution_failure = (sc.OperationNotSupported, sc.OclLaunchOutOfResources, sc.CudaLaunchOutOfResources, sc.MemObjectAllocationFailure, sc.InvalidWorkGroupSize, sc.OutOfHostMemory, sc.InvalidValue)
dtype=sc.float32
def sanitize(string, keep_chars = ['_']):
string = string.replace(' ', '_').replace('-', '_').lower()
string = "".join(c for c in string if c.isalnum() or c in keep_chars).rstrip()
@@ -43,7 +45,7 @@ def expspace(a,b,N,r=128):
def benchmark(template, tree, operation=sc.templates.gemm_nn):
queue = tree.context.queues[0]
queue.profiles[template, sc.float32] = sc.profile(template, sc.float32, queue)
queue.profiles[template, dtype] = sc.profile(template, dtype, queue)
times = []
total = 0
#Warm-up
@@ -66,33 +68,33 @@ def benchmark(template, tree, operation=sc.templates.gemm_nn):
def tree_of(template, sizes, context):
if issubclass(template, sc.templates.elementwise_1d):
N, = sizes
x = sc.empty(N, dtype=sc.float32, context=context)
y = sc.empty(N, dtype=sc.float32, context=context)
x = sc.empty(N, dtype=dtype, context=context)
y = sc.empty(N, dtype=dtype, context=context)
return sc.assign(y, x + y), (x, y)
elif issubclass(template, sc.templates.reduce_1d):
N, = sizes
x = sc.empty(N, context=context)
y = sc.empty(N, context=context)
x = sc.empty(N, dtype=dtype, context=context)
y = sc.empty(N, dtype=dtype, context=context)
return sc.dot(x, y), (x, y)
elif issubclass(template, sc.templates.elementwise_2d):
M, N = sizes
A = sc.empty((M,N), context=context)
B = sc.empty((M,N), context=context)
A = sc.empty((M,N), dtype=dtype, context=context)
B = sc.empty((M,N), dtype=dtype, context=context)
return A + B, (A, B)
elif issubclass(template, sc.templates.reduce_2d):
T = template is sc.templates.reduce_2d_cols
M, N = sizes[::-1] if T else sizes
A = sc.empty((M,N), context=context)
x = sc.empty(N, context=context)
y = sc.empty(M, context=context)
A = sc.empty((M,N), dtype=dtype, context=context)
x = sc.empty(N, dtype=dtype, context=context)
y = sc.empty(M, dtype=dtype, context=context)
return sc.assign(x, sc.dot(A.T, y)) if T else sc.assign(y, sc.dot(A, x)), (A, x, y)
elif issubclass(template, sc.templates.gemm):
AT = template is sc.templates.gemm_tn or template is sc.templates.gemm_tt
BT = template is sc.templates.gemm_nt or template is sc.templates.gemm_tt
M, N, K = sizes
C = sc.empty((M,N), context=context)
A = sc.empty((K, M) if AT else (M, K), context=context)
B = sc.empty((N, K) if BT else (K, N), context=context)
C = sc.empty((M,N), dtype=dtype, context=context)
A = sc.empty((K, M) if AT else (M, K), dtype=dtype, context=context)
B = sc.empty((N, K) if BT else (K, N), dtype=dtype, context=context)
AA = A.T if AT else A
BB = B.T if BT else B
return sc.assign(C, sc.dot(AA, BB)), (A, B, C)

12
tune/android/tune/tune.py
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@@ -46,10 +46,11 @@ def pow2range(a, b):
class Tuner:
def __init__(self, logger, device, operation, json_path, progress_bar):
def __init__(self, logger, device, operation, dtype, json_path, progress_bar):
self.logger = logger
self.device = device
self.operation = operation
self.dtype = dtype
self.json_path = json_path
self.progress_bar = progress_bar
@@ -57,7 +58,7 @@ class Tuner:
def run(self, level = 'intermediate'):
assert level in ['simple', 'intermediate', 'full']
tools.dtype = self.dtype
device = self.device
operation = self.operation
context = sc.driver.context(device)
@@ -65,6 +66,7 @@ class Tuner:
if self.logger:
self.logger.info("----------------")
self.logger.info(operation.__name__.replace('_','-').upper())
self.logger.info(tools.dtype.__name__.upper())
self.logger.info("----------------")
#BLAS1 training sizes
@@ -116,7 +118,7 @@ class Tuner:
profiles, X, Y = [], [], []
#Restore progress
savepath = os.path.join('save', operation.__name__)
savepath = os.path.join('save', tools.dtype.__name__, operation.__name__)
if not os.path.exists(savepath):
os.makedirs(savepath)
try:
@@ -202,8 +204,8 @@ class Tuner:
operation_name = operation.__name__
if operation_name not in json_data:
json_data[operation_name] = {}
json_data[operation_name]['float32'] = {}
D = json_data[operation_name]['float32']
json_data[operation_name][tools.dtype.__name__] = {}
D = json_data[operation_name][tools.dtype.__name__]
if len(profiles) > 1:
clf, nrmse = model.train(X, Y, profiles)
D['predictor'] = [{'children_left': e.tree_.children_left.tolist(),

14
tune/main.py
View File

@@ -30,6 +30,8 @@ def parse_arguments():
parser = argparse.ArgumentParser()
parser.add_argument("-d", "--device", default=0, type=int, help='Device to tune for')
parser.add_argument("-j", "--json", default='', type=str)
parser.add_argument('--float32', action='store_true', help='Tune 32-bits FLOAT')
parser.add_argument('--float64', action='store_true', help='Tune 64-bits FLOAT')
parser.add_argument('--elementwise_1d', action='store_true', help='Tune ELEMENTWISE [1D]')
parser.add_argument('--elementwise_2d', action='store_true', help='Tune ELEMENTWISE [2D]')
parser.add_argument('--reduce_1d', action='store_true', help='Tune REDUCE [1D]')
@@ -54,7 +56,12 @@ def parse_arguments():
operations = ['elementwise_1d', 'reduce_1d', 'elementwise_2d', 'reduce_2d_rows', 'reduce_2d_cols', 'gemm_nn', 'gemm_tn', 'gemm_nt', 'gemm_tt']
operations = [getattr(sc.templates,op) for op in operations if getattr(args, op)]
return (device, operations, args.json)
#Dtypes
dtypes = []
if args.float32: dtypes+=[sc.float32]
if args.float64: dtypes+=[sc.float64]
return (device, operations, dtypes, args.json)
class ProgressBar:
@@ -91,8 +98,9 @@ if __name__ == "__main__":
logger.setLevel(logging.INFO)
sc.driver.default.queue_properties = sc.driver.PROFILING_ENABLE
device, operations, json = parse_arguments()
device, operations, dtypes, json = parse_arguments()
for operation in operations:
tuner = Tuner(logger, device, operation, json, ProgressBar(30, metric_name_of(operation)))
for dtype in dtypes:
tuner = Tuner(logger, device, operation, dtype, json, ProgressBar(30, metric_name_of(operation)))
tuner.run(level='intermediate')