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Test Suite for Evaluating Performance of MPI Implementations That Support MPI_THREAD_MULTIPLE By: Rajeev Thakur and William Gropp Argonne National Laboratory, USA. Presenter : Nageeb Yahya Alsurmi GS21565 Ameen Mohammad GS22872 Yasien Ahmad GS24259
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Test Suite for Evaluating Performance of MPI Implementations That Support MPI_THREAD_MULTIPLE By: Rajeev Thakur and William Gropp Argonne National Laboratory, USA Presenter : NageebYahyaAlsurmi GS21565 Ameen Mohammad GS22872 Yasien Ahmad GS24259 AtiqAlemadi GS21798 Lecturer:Dr. NOR ASILAH WATI ABDUL HAMID HPC SKR 5800 UPM University
Outline • Introduction • Literature Review • Problem Statement • Problem Objective • MPI and threads overview • Methodology • Test Suite ( 8- benchmark) • Experimental Result • Conclusion and Future work • References
Introduction 1/2 • With thread-safe MPI implementations becoming increasingly common. • MPI process is a process that may be multithreaded. • Each thread can issue MPI calls. • Threads are not separately addressable: a rank in a send or receive call identifies a process, not a thread. • A message sent to a process can be received by any thread in this process. • The user can make sure that two threads in the same process will not issue conflicting communication calls by using distinct communicators at each thread.
Introduction 2/2 • The two main requirements for a thread-compliant implementation: • 1- All MPI calls are thread-safe. • 2- Blocking MPI calls will block the calling thread only, allowing another thread to execute, if available.
Literature Review • The MPI benchmarks from Ohio State University only contain a multithreaded latency test. • The latency test is a ping-pong test with one thread on the sender side and two (or more) threads on the receiver side. • There are a number of MPI benchmarks exist, such as SKaMPI and Intel MPI Benchmarks, but they do not measure the performance of multithreaded MPI programs (this is the key issue of this paper).
Problem statement • With thread-safe MPI implementations becoming increasingly common, users are able to write multithreaded MPI programs that make MPI calls concurrently from multiple threads. • Developing a thread-safe MPI implementation is a fairly complex task. • Users, therefore, need a way to measure the outcome and determine how efficiently an implementation can support multiple threads.
Objective • The authors proposed a test suite that can shed light on the performance of an MPI implementation in the multithreaded case. • To illustrate the results provided by the test suite and how these results should be analyzed
Overview of MPI and Threads 1/2 • To understand the test suite you have first to understand the thread-safety specification in MPI. • MPI defines four “levels” of thread safety: • 1-MPI_THREAD_SINGLE Each process has a single thread of execution. • 2. MPI_THREAD_FUNNELED A process may be multithreaded, but only the Main thread that initialized MPI may make MPI calls. T T P2 P1 MPI Call MPI Call P2 P1 Tm T MPI Call MPI Call T Tm T T
Overview of MPI and Threads2/2 • 3. MPI THREAD SERIALIZED A process may be multithreaded, but only one thread at a time may make MPI calls. • 4. MPI THREAD MULTIPLE A process may be multithreaded, and multiple threads may simultaneously call MPI functions (with some restrictions mentioned below). 1 MPI Call T 2 MPI Call T P1 3 MPI Call T T MPI Call P1 T MPI Call T MPI Call Our case
thread-safe. • if your code access the same memory location from multiple threads with protection, it is most likely thread-safe. • A blocked MPI call in one thread will not obstruct MPI operations in other threads. • the risk that one thread will interfere and modify data elements of another thread is eliminated. • This is fairly minimal thread safety since you must ensure that your programs logic is thread safe, that is if your application is multithreaded. • In this context thread safety means that execution of multiple threads does not in itself corrupt the state of your objects.
Blocking MPI functions • Deadlock occurs when a process holds a lock and then attempts to acquire a second lock. If the second lock is already held by another process, the first process will be blocked. If the second process then attempts to acquire the lock held by the first process, the system has "deadlocked": no progress will ever be made • They cause blocking, which means some threads/processes have to wait until a lock (or a whole set of locks) is released Process 0 Process 1 Thread 1 Thread 0 Thread 1 Thread 0 MPI_Recv(src1) MPI_Send(dest1) MPI_Recv(src0) MPI_Send(dest0) Buffer full Wait for thread 1 to complete the send operation to start reading from the buffer The buffer is full but still a data are sending so thread 1 wait for thread 0 to empty (read) the buffer
MPI implementations • There are many MPI implementations but in this paper , just used four implementations: • MPICH2 it’s a library and portable • It’s a library (not compiler), It can achieve parallelism using networked machines or using multitasking on a single machine. • portable implementation of MPI, a standard for message-passing . • can be used for communication between processors. • OPEN MPI • merger between three well-known MPI implementations (FT-MPI, LA-MPI, LAM/MPI). • (MPI) SUN MPI run on SUN machines • It is Sun Microsystems' implementation of MPI • IBM’s MPI runs on IBM SP systems and AIX workstation clusters.
Experiment test: • The test suit has carried on multiple MPI implementation with different platforms. • Linux Cluster (4node,AMD OpetronDualCore2.8GHz) • MPICH2 V 1.0.7 , OpenMPI V1.2.6 • Gigabit Ethernet networking • SUN T5120 server with 8 Core 1.4GHz (SUN cluster) • SUN MPI. • IBM p566+ SMP has 8 Power4+ CPU 1.7GHz • IBM MPI
The Test Suite • The test has three categorization: • 1-Cost of thread safety test • 1-1 MPI THREAD MULTIPLE overhead • 2-Concurrent progress test • 2-1 Concurrent bandwidth • 2-2 Concurrent latency • 2-3 Message Rate • 2-4 Concurrent short-long messages • 3-Computation/ communication tests • 3-1 Computation/ communication overlap • 3-2 Concurrent collective operation • 3-3 Concurrent collective and computation
1-Cost of thread safety test • MPI THREAD MULTIPLE Overhead test (small messages) • Initializing MPI with just MPI_Init and initializing it with MPI_Init_ thread for MPI-THREAD-MULTIPLE • Ping pong Latency (command : mprun –np 2 ./latency) • Command (with-thread) : mprun –np 2 ./latency_threaded Ping Ping Pong Pong The difference MPI_Init(&argc,&argv) MPI_Init_thread(MPI_THREAD_MULTIPLE); Without Thread With Thread = Overhead
1-Cost of thread safety result • MPI THREAD MULTIPLE Overhead Results: • Linux Cluster -- MPICH2 & OpenMPI overhead average <= o.5 us • IBM cluster -- IBM MPI Overhead avearage < 0.25 us • SUN Cluster --- SUN MPI Overhead avearage > 3 us • overhead was observed is to ensure the thread safety for the MPI_THREAD_MULTIPLE case, which is typically implemented by acquiring and releasing mutex locks. P P T T P P
2-Concurrent progress test 1/3 • 2-1- concurrent bandwidth (cumulative bandwidth) • Test on Large Messages (point to point communication) • Process ( 4 processes at each node) • Threads ( 2 processes each one has 2 threads) Large message Large message P1 P1 P1 T1 T1 T1 T1 T1 P1 P1 T2 T2 T2 T2 T2 P2 P2 P2 P2 P4 P3 P3 P3 T1 T1 T1 T1 T2 T2 P4 P4 T2 + + cumulative bandwidth
2-1 concurrent bandwidth result 2/3 • Command : mprun –np 8 ./bandwidth • Command : mprun –np 2 ./bandwidth_th 4 (thread version) • how much thread locks affect the cumulative bandwidth. • Linux Cluster (AMD Opetron two dual-core) • MPICH2 no measurable difference in bandwidth between threads and processes. • OpenMPI there is a decline in bandwidth with threads. • IBM MPI & SUN MPI there is a substantial decline • (more than 50% in some cases) in the bandwidth when threads were used. • It is harder to provide low overhead in these shared memory environments because the communication bandwidths are so high
2-2- concurrent bandwidth graph 3/3 • Sun & IBM ,It is harder to provide low overhead in these shared memory environments because the communication bandwidths are so high , Bandwidth = size/time
2-2-concurrent latency test 1/3 • This is similar to the concurrent bandwidth test except that it measures the time for individual short messages. Short message series Short message series P1 P1 P1 T1 T1 T1 T1 T1 P1 P1 T2 T2 T2 T2 T2 P2 P2 P2 P2 P4 P3 P3 P3 T1 T1 T1 T1 T2 T2 P4 P4 T2 Mutti threading Process
2-2-concurrent latency result 2/3 • overhead in latency when using concurrent threads instead of processes • Linux cluster • MPICH2 overhead is about 20 μs. • Open MPI overhead is about 30 μs. • IBM MPI & SUN MPI • the latency with threads is about 10 times the latency with processes. • But still the IBM & SUN has the low latency compared with MPICH & Open MPI.
2-2-Concurrent Latency Graph 3/3 • But still the IBM & SUN has the low latency compared with MPICH & Open MPI. • Careful design and tuning of code is needed to minimize the overhead
2-3 Message Rate (MR) • This test is similar to the concurrent latency test except that it measures the message rate for zero-byte sends. • The individual message rates are summed to determine the total message rate. • Sun &IBM SMPs., • the overall MR are much • higher because all • communication takes place within a node using shared memory. • MPICH has best MR.
2-4 Concurrent Short-Long Messages Test1/2 • This test is a blend of the concurrent bandwidth and concurrent latency tests • This test tests the fairness of thread scheduling and locking. • If they were fair, one would expect each of the short messages to take roughly the same amount of time. Short message series Short message series P0 P1 P1 T1 T1 T1 T1 T1 T2 T2 T2 T2 T2 P2 P0 P2 P1 P1 P2 Long message T1 T2 P3 Long message Multi Threads Process
2-4 Concurrent Short-Long Messages Results2/2 • This result demonstrates that, in the threaded. case, locks are fairly held and released and that the thread blocked in the long message send does not block the other thread.
3-1 Computation/ communication overlap test1/3 • To study the impact of non-blocking communication (send and recive) over computation operation • This technique effectively simulates asynchronous progress by the MPI implementation. • If total time ( threading mode) < total time (non threading) there is no overlap communication with computation.
3-1Computation/ communication overlap result 3/3 IBMonly the one which has overlap because it has higher overhead of multiple thread and extra overhead for switching between threads
3-2 Concurrent Collectives test1/3 • compares the performance of concurrent calls to a collective function (MPI_Allreduce) issued from multiple threads to that when issued from multiple processes. P1 P1 P1 Process
3-2 Concurrent Collectives test 2/3 • Thread version – collective operation MPI_Allreduce P1 T1 T2 P1 P1 T1 T1 T2 T2 Multi Threads
3-2 Concurrent Collectives result 3/3 • results on the Linux cluster. MPICH2 has relatively small overhead for the threaded version, compared with Open MPI.
3-3 Concurrent Collectives and Computation (final test) • evaluates the ability to use a thread to hide the latency of a collective operation while using all available processors to perform computations. (collective communication + computation) • Test 1: MPI_Allreduce function used for collective with computation • Test 2: no MPI_ allreduce used only computation operation. • Then compared two tests (the higher is the better). • MPICH2 demonstrates a better ability than Open MPI to hide the latency of the MPI_allreduce.
Conclusion & future work • MPI implementations supporting MPI THREAD MULTIPLE become increasingly available. • The Authors have developed such a test suite and show its performance on multiple platforms and implementations • Design and tuning of code is needed to minimize the overhead. • The results indicate • Good performance with MPICH2 and Open MPI on Linux clusters. • Poor performance with IBM and Sun MPI on IBM and Sun SMP systems • The Authors plan to add more tests to the suite, such as to measure the overlap of computation/communication with the MPI-2 file I/O and connect-accept features.
References • 1. Francisco Garc´ıa, Alejandro Calder´on, and Jes´us Carretero. MiMPI: A multithreadsafe • implementation of MPI. In Recent Advances in Parallel Virtual Machine and • Message Passing Interface, 6th European PVM/MPI Users’ Group Meeting, pages • 207–214. Lecture Notes in Computer Science 1697, Springer, September 1999. • 2. William Gropp and Rajeev Thakur. Issues in developing a thread-safe MPI implementation. • In Recent Advances in Parallel Virtual Machine and Message Passing • Interface, 13th European PVM/MPI Users’ Group Meeting, pages 12–21. Lecture • Notes in Computer Science 4192, Springer, September 2006. • 3. Intel MPI benchmarks. http://www.intel.com. • 4. OSU MPI benchmarks. http://mvapich.cse.ohio-state.edu/benchmarks. • 5. Boris V. Protopopov and Anthony Skjellum. A multithreaded message passing • interface (MPI) architecture: Performance and program issues. Journal of Parallel • and Distributed Computing, 61(4):449–466, April 2001. • 6. Ralf Reussner, Peter Sanders, and Jesper Larsson Tr¨aff. SKaMPI: A comprehensive • benchmark for public benchmarking of MPI. Scientific Programming, 10(1):55–65, • January 2002.
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