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Cell Broadband Processor

Cell Broadband Processor

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Cell Broadband Processor

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  1. Cell Broadband Processor Daniel Bagley Meng Tan

  2. Agenda • General Intro • History of development • Technical overview of architecture • Detailed technical discussion of components • Design choices • Other processors like the cell • Programming for the cell

  3. History of Development • Sony Playstation2 • Announce March 1999 • Released March 2000 in Japan • 128bit “Emotion Engine” • 294mhz, MIPS CPU • Single Precision FP Optimizations • 6.2gflops

  4. History Continued • Partnership between Sony, Toshiba, IBM • Summer of 2000 – High level development talks • Initial goal of 1000x PS2 Power • March 2001, Sony-IBM-Toshiba design center opened • $400m investment.

  5. Overall Goals for Cell • High performance in multimedia apps • Real time performance • Power consumption • Cost • Available by 2005 • Avoid memory latency issues associated with control structures

  6. The Cell itself • Power PC based main core (PPE) • Multiple SPEs • On die memory controller • Inter-core transport bus • High speed IO

  7. Cell Die Layout

  8. Cell Implementation • Cell is an architecture • Preliminary PS3 Implementation • 1 PPE • 7 SPE (1 Disabled for yield increase) • 221 mm² die size on a 90 nm process • Clocked at 3-4ghz • 256GFLOPS Single Precision @ 4ghz

  9. Why a Cell Architecture • Follows a trend in computing architecture • Natural extension of dual and multi-core • Extremely low hardware overhead • Software controllable • Specialized hardware more useful for multimedia

  10. Possible Uses • Playstation3 (Obviously) • Blade servers (IBM) • Amazing single precision FP performance • Scientific applications • Toshiba HDTV products

  11. Power Processing Element • PowerPC instruction set with AltiVec • Used for general purpose computing and controlling SPE’s • Simultaneous Multithreading • Separate 32 KB L1 Caches and unified 512 KB L2 Cache

  12. PPE (cont.) • Slow but power efficient PowerPC instruction set implementation • Two issue in-order instruction fetch • Conspicuous lack of instruction window • Compare to conventional PowerPC implementations (G5) • Performance depends on SPE utilization

  13. Synergistic Processing Element (SPE) • Specialized hardware • Meant to be used in parallel • (7 on PS3 implementation) • On chip memory (256kb) • No branch prediction • In-order execution • Dual issue

  14. SPE Architecture • 0.99µm2 on 90nm Process • 128 registers (128 bits wide) • Instructions assumed to be 4x 32bit • Variant of VMX instruction set • Modified for 128 registers • On chip memory is NOT a cache

  15. SPE Execution • Dual issue, in-order • Seven execution units • Vector logic • 8 single precision operations per cycle • Significant performance hit for double precision

  16. SPE Execution Diagram

  17. SPE Local Storage Area • NOT a cache • 256kb, 4 x 64kb ECC single port SRAM • Completely private to each SPE • Directly addressable by software • Can be used as a cache, but only with software controls • No tag bits, or any extra hardware

  18. SPE LS Scheduling • Software controlled DMA • DMA to and from main memory • Scheduling a HUGE problem • Done primarily in software • IBM predicts 80-90% usage ideally • Request queue handles 16 simultaneous requests • Up to 16 kb transfer each • Priority: DMA, L/S, Fetch • Fetch / execute parallelism

  19. SPE Control Logic • Very little in comparison • Represents shift in focus • Complete lack of branch prediction • Software branch prediction • Loop unrolling • 18 cycle penalty • Software controlled DMA

  20. SPE Pipeline • Little ILP, and thus little control logic • Dual issue • Simple commit unit (no reorder buffer or other complexities) • Same execution unit for FP/int

  21. SPE Summary • Essentially small vector computer • Based on Altivec/VMX ISA • Extensions for DMA and LS management • Extended for 128x 128bit registerfile • Uniquely suited for real time applications • Extremely fast for certain FP operations • Offload a large amount on to compiler / software.

  22. Element Interconnect Bus • 4 concentric rings connecting all Cell elements • 128-bit wide interconnects

  23. EIB (cont.) • Designed to minimize coupling noise • Rings of data traveling in alternating directions • Buffers and repeaters at each SPE boundary • Architecture can be scaled up with increased bus latency

  24. EIB (cont.) • Total bandwidth at ~200GB/s • EIB controller located physically in center of chip between SPE’s • Controller reserves channels for each individual data transfer request • Implementation allows for SPE extension horizontally

  25. Memory Interface • Rambus XDR memory to keep Cell at full utilization • 3.2 Gbps data bandwidth per device connected to XDR interface • Cell uses dual channel XDR with four devices and 16-bit wide buses to achieve 25.2 GB/s total memory bandwidth

  26. Input / Output Bus • Rambus FlexIO Bus • IO interface consists of 12 unidirectional byte lanes • Each lane supports 6.4 GB/s bandwidth • 7 outbound lanes and 5 inbound lanes

  27. Design Choices • In-order execution • Abandoning ILP • ILP – 10-20% increase per generation • Reducing control logic • Real time responsiveness • Cache Design • Software configuration on SPE • Standard L2 cache on PPE

  28. Cell Programming Issues • No Cell compiler in existence to manage utilization of SPE’s at compile time • SPE’s do not natively support context switching. Must be OS managed. • SPE’s are vector processors. Not efficient for general-purpose computation. • PPE’s and SPE’s use different instruction sets.

  29. Cell Programming (cont.) • Functional Offload Model • Simplest model for Cell programming • Optimize existing libraries for SPE computation • Requires no rebuild of main application logic which runs on PPE

  30. Cell Programming (cont.) • Device Extension Model • Take advantage of SPE DMA • Use SPE’s as interfaces to external devices

  31. Cell Programming (cont.) • Computational Acceleration Model • Traditional super-computing methods using Cell • Shared memory or message passing paradigm for accelerating inherently parallel math operations • Can overwrite intensive math libraries without rewriting applications

  32. Cell Programming (cont.) • Streaming model • Use Cell processor as one large programmable pipeline • Partition algorithms into logically sensible steps. Execute each separately, in serial, on separate processors.

  33. Cell Programming (cont.) • Asymmetric Thread Runtime Model • Abstract Cell architecture away from programmer. • Use OS to use processors to each run different threads.

  34. Sample Performance • Demonstration physics engine for real-time game • http://www.research.ibm.com/cell/whitepapers/cell_online_game.pdf • 182 Compute to DMA ratio on SPE’s • For the right tasks, Cell architecture can be extremely efficient.