Update MP UT to support arbitrary # of GPUs; multiple bugfixes (#16)

* Fixing temp file creation/deletion for Clique kernel mode.

* Refactoring of MP unit tests; include bugfixes and general support for any number of GPUs

* GroupCall MP UT properly quits when too many devices specified

* MP UT will programmatically set NCCL_COMM_ID if not specified; updated install script

[ROCm/rccl commit: d00b7d17bd]
This commit is contained in:
Stanley Tsang
2021-02-05 17:49:25 -07:00
committed by GitHub
szülő fe8923ebba
commit f152c8d160
23 fájl változott, egészen pontosan 538 új sor hozzáadva és 716 régi sor törölve
@@ -13,26 +13,35 @@ namespace CorrectnessTests
class BroadcastMultiProcessCorrectnessTest : public MultiProcessCorrectnessTest
{
public:
static void ComputeExpectedResults(Dataset& dataset, int const root, int const rank)
static void ComputeExpectedResults(Dataset& dataset, int const root, std::vector<int> const& ranks)
{
// Root has the answer; share it via host memcpy's
if (rank == root)
for (int h = 0; h < ranks.size(); h++)
{
HIP_CALL(hipMemcpy(dataset.expected[rank], dataset.inputs[rank],
dataset.NumBytes(), hipMemcpyDeviceToHost));
for (int i = 0; i < dataset.numDevices; i++)
int rank = ranks[h];
// Root has the answer; share it via host memcpy's
if (rank == root)
{
if (i == rank) continue;
memcpy(dataset.expected[i], dataset.expected[root], dataset.NumBytes());
HIP_CALL(hipMemcpy(dataset.expected[rank], dataset.inputs[rank],
dataset.NumBytes(), hipMemcpyDeviceToHost));
for (int i = 0; i < dataset.numDevices; i++)
{
if (i == rank) continue;
memcpy(dataset.expected[i], dataset.expected[root], dataset.NumBytes());
}
break;
}
}
}
void TestBroadcast(int rank, Dataset& dataset)
void TestBroadcast(int rank, Dataset& dataset, bool& pass)
{
SetUpPerProcess(rank, ncclCollBroadcast, comms[rank], streams[rank], dataset);
if (numDevices > numDevicesAvailable) return;
if (numDevices > numDevicesAvailable)
{
pass = true;
return;
}
Barrier barrier(rank, numDevices, std::atoi(getenv("NCCL_COMM_ID")));
@@ -41,7 +50,7 @@ namespace CorrectnessTests
{
// Prepare input / output / expected results
FillDatasetWithPattern(dataset, rank);
ComputeExpectedResults(dataset, root, rank);
ComputeExpectedResults(dataset, root, std::vector<int>(1, rank));
// Launch the reduction (1 process per GPU)
ncclResult_t res = ncclBroadcast(dataset.inputs[rank],
@@ -53,7 +62,7 @@ namespace CorrectnessTests
HIP_CALL(hipStreamSynchronize(streams[rank]));
// Check results
ValidateResults(dataset, rank);
pass = ValidateResults(dataset, rank);
// Ensure all processes have finished current iteration before proceeding
barrier.Wait();