Review: Where are We Now?

1. Review: Where are We Now? • Multiprocessor – multiple processors with a single shared address space • Cluster – multiple computers (each with their own address space) connected over a local area network (LAN) functioning as a single system Processor Processor Output Output Control Control Memory Memory Datapath Input Input Datapath

2. Multiprocessor Basics • Q1 – How do they share data? • Q2 – How do they coordinate? • Q3 – How scalable is the architecture? How many processors?

3. Single Bus (Shared Address UMA) Multi’s • Caches are used to reduce latency and to lower bus traffic • Write-back caches used to keep bus traffic at a minimum • Must provide hardware to ensure that caches and memory are consistent (cache coherency) • Must provide a hardware mechanism to support process synchronization Proc1 Proc2 Proc3 Proc4 Caches Caches Caches Caches Single Bus Memory I/O

4. Proc1 Proc2 ProcN Snoop Snoop Snoop DCache DCache DCache Single Bus Memory I/O Multiprocessor Cache Coherency • Cache coherency protocols • Bus snooping – cache controllers monitor shared bus traffic with duplicate address tag hardware (so they don’t interfere with processor’s access to the cache)

5. Bus Snooping Protocols • Multiple copies are not a problem when reading • Processor must have exclusive access to write a word • What happens if two processors try to write to the same shared data word in the same clock cycle? The bus arbiter decides which processor gets the bus first (and this will be the processor with the first exclusive access). Then the second processor will get exclusive access. Thus, bus arbitration forces sequential behavior. • This sequential consistency is the most conservative of the memory consistency models. With it, the result of any execution is the same as if the accesses of each processor were kept in order and the accesses among different processors were interleaved. • All other processors sharing that data must be informed of writes

6. Handling Writes Ensuring that all other processors sharing data are informed of writes can be handled two ways: • Write-update (write-broadcast) – writing processor broadcasts new data over the bus, all copies are updated • All writes go to the bus  higher bus traffic • Since new values appear in caches sooner, can reduce latency • Write-invalidate– writing processor issues invalidation signal on bus, cache snoops check to see if they have a copy of the data, if so they invalidate their cache block containing the word (this allows multiple readers but only one writer) • Uses the bus only on the first write  lower bus traffic, so better use of bus bandwidth

7. Main Mem A Main Mem A Main Mem A Main Mem A Proc 2 Proc 1 Proc 2 Proc 2 Proc 1 Proc 1 Proc 1 Proc 2 A S A I A S A M A M A I A I A I Write-Invalidate CC Examples • I = invalid (many), S = shared (many), M = modified (only one) 3. snoop sees read request for A & lets MM supply A 1. read miss for A 1. write miss for A 2. writes A & changes its state to M 4. gets A from MM & changes its state to S 4. change A state to I 2. read request for A 3. P2 sends invalidate for A 1. write miss for A 3. snoop sees read request for A, writes-back A to MM 1. read miss for A 4. gets A from MM & changes its state to M 2. writes A & changes its state to M 4. change A state to I 5. change A state to I 5. P2 sends invalidate for A 2. read request for A 3. P2 sends invalidate for A

8. SMP Data Miss Rates • Shared data has lower spatial and temporal locality • Share data misses often dominate cache behavior even though they may only be 10% to 40% of the data accesses 64KB 2-way set associative data cache with 32B blocks Hennessy & Patterson, Computer Architecture: A Quantitative Approach

9. Proc1 Proc2 A B 4 word cache block Block Size Effects • Writes to one word in a multi-word block mean • either the full block is invalidated (write-invalidate) • or the full block is exchanged between processors (write-update) • Alternatively, could broadcast only the written word • Multi-word blocks can also result in false sharing: when two processors are writing to two different variables in the same cache block • With write-invalidate false sharing increases cache miss rates • Compilers can help reduce false sharing by allocating highly correlated data to the same cache block

10. Other Coherence Protocols • There are many variations on cache coherence protocols • Another write-invalidate protocol used in the Pentium 4 (and many other micro’s) is MESI with four states: • Modified – same • Exclusive – only one copy of the shared data is allowed to be cached; memory has an up-to-date copy • Since there is only one copy of the block, write hits don’t need to send invalidate signal • Shared – multiple copies of the shared data may be cached (i.e., data permitted to be cached with more than one processor); memory has an up-to-date copy • Invalid – same

11. Process Synchronization • Need to be able to coordinate processes working on a common task • Lock variables (semaphores) are used to coordinate or synchronize processes • Need an architecture-supported arbitration mechanism to decide which processor gets access to the lock variable • Single bus provides arbitration mechanism, since the bus is the only path to memory – the processor that gets the bus wins • Need an architecture-supported operation that locks the variable • Locking can be done via an atomic swap operation (processor can both read a location and set it to the locked state – test-and-set – in the same bus operation)

12. Spin Spin Lock Synchronization Read lock variable unlock variable: set lock variable to 0 No Unlocked? (=0?) Yes Finish update of shared data atomic operation Try to lock variable using swap: read lock variable and set it to locked value (1) . . . No Yes Begin update of shared data Succeed? (=0?) The single winning processor will read a 0 - all others processors will read the 1 set by the winning processor

13. Review: Summing Numbers on a SMP • Pn is the processor’s number, vectors A and sum are shared variables, i is a private variable, half is a private variable initialized to the number of processors sum[Pn] = 0; for (i = 1000*Pn; i< 1000*(Pn+1); i = i + 1) sum[Pn] = sum[Pn] + A[i]; /* each processor sums its /* subset of vector A repeat /* adding together the /* partial sums synch(); /*synchronize first if (half%2 != 0 && Pn == 0) sum[0] = sum[0] + sum[half-1]; half = half/2 if (Pn<half) sum[Pn] = sum[Pn] + sum[Pn+half]; until (half == 1); /*final sum in sum[0]

14. P0 P1 P2 P3 P4 P5 P6 P7 P8 P9 sum[P0] sum[P1] sum[P2] sum[P3] sum[P4] sum[P5] sum[P6] sum[P7] sum[P8] sum[P9] P0 P1 P2 P3 P4 An Example with 10 Processors • synch(): Processors must synchronize before the “consumer” processor tries to read the results from the memory location written by the “producer” processor • Barrier synchronization – a synchronization scheme where processors wait at the barrier, not proceeding until every processor has reached it

15. Barrier Implemented with Spin-Locks • n is a shared variable initialized to the number of processors,count is a shared variable initialized to 0, arrive and depart are shared spin-lock variables where arrive is initially unlocked and depart is initially locked lock(arrive); count := count + 1; /* count the processors as if count < n /* they arrive at barrier then unlock(arrive) else unlock(depart); procedure synch() lock(depart); count := count - 1; /* count the processors as if count > 0 /* they leave barrier then unlock(depart) else unlock(arrive);

16. Spin-Locks on Bus Connected ccUMAs • With bus based cache coherency, spin-locks allow processors to wait on a local copy of the lock in their caches • Reduces bus traffic – once the processor with the lock releases the lock (writes a 0) all other caches see that write and invalidate their old copy of the lock variable. Unlocking restarts the race to get the lock. The winner gets the bus and writes the lock back to 1. The other caches then invalidate their copy of the lock and on the next lock read fetch the new lock value (1) from memory. • This scheme has problems scaling up to many processors because of the communication traffic when the lock is released and contested

17. Commercial Single Backplane Multiprocessors

18. Summary • Key questions • Q1 - How do processors share data? • Q2 - How do processors coordinate their activity? • Q3 - How scalable is the architecture (what is the maximum number of processors)? • Bus connected (shared address UMA’s(SMP’s)) multi’s • Cache coherency hardware to ensure data consistency • Synchronization primitives for synchronization • Scalability of bus connected UMAs limited (< ~ 36 processors) because the three desirable bus characteristics • high bandwidth • low latency • long length are incompatible • Network connected NUMAs are more scalable