1. Multi-core systems System Architecture COMP25212 Daniel Goodman Advanced Processor Technologies Group

2. Processors Designs  Power  Single Threaded Performance  Throughput  Reliability ......

3. Classifying Processors  SISD Single Instruction Single Data Uniprocessor  SIMD Single Instruction Multiple Data Vector processor & Vector operations (MMX & SSE)  MIMD Multiple Instructions Multiple Data Multi-cores (multiprocessors)  MISD (not known)  SPMD: Single Program Multiple Data (MIMD plus only one program) clusters

4. Classifying Processors  RISC Reduced instruction set Small number of very fast simple instructions Complex instructions are constructed from many smaller instructions  CISC Complex instruction set Lots of instructions Can be slow, but do a lot of work per instruction

5. Graphics Processing Units (GPU)  HD video and games are computationally very demanding (Beyond even the best CPU’s)  Extremely parallel, each pixel is independent  Quite different emphasis and evolution for GPUs Fine to perform non-graphics tasks poorly or not at all Large number of cores and each highly multithreaded (768 -1024 concurrent threads per Nvidia core) Additional threads are queued till the earlier threads complete Shared register file Each core is SIMD No coherency between cores No communication between groups of threads Very fast memory access

6. Graphics Processing Units (GPU)

7. Coalesced Memory Access

8. Un-Coalesced Memory Access

9. SpiNNaker Massively Parallel System

10. Fabricated SpiNNaker CMP Fabricated in UMC 130nm L130E CMP Die Area - 101.64 sq.mm Over 100 million transistors Power consumption of 1W at 1.2V when all the processor cores are operating Peak Performance – 4 GIPS

11. Constructing Clusters, Data Centres and Super Computers

12. Composing Multi-cores QPI or HT Input/Output Hub Motherboard Multi-core Memory (DRAM) Input/Output Hub Multi-core Chip Memory (DRAM) Multi-core Chip Memory (DRAM) Multi-core Chip Memory (DRAM)

13. Composing Multiple Computers... Interconnection Network

14. Clusters/Super Computers/Data Centres  All terms overloaded and misused  Have lots of CPU’s on lots of Mother boards  Clusters/Super Computers are used to run one large task very quickly eg. A simulation  Cluster/Farms/Data centres do thousands of independent tasks in parallel eg. Google Mail  The distinction becomes blurred with services such as Google  Main difference is the network between CPU’s

15. Building a Cluster/SC/DC Large numbers of self contained computers in a small form factor These are optimised for cooling and power efficiency Racks house 10’s – 100’s of CPU’s They normally also contain separate units for networking and power distribution They are self contained

16. Building a Cluster/SC/DC Sometimes a rack is not big enough How many new computers a day go into a data centre? What does this mean for reliability?

17. Building a Cluster/SC/DC  Join Lots of racks  Add power distribution, network and cooling  For Super Computers add racks dedicated to storage

18. K Super Computer  Water cooled  6D network for fault tolerance  RISC processors (Sparc64 VIII fx)  90,000 processors

19. Questions ?