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Special-Purpose Multithreaded Chip Multiprocessors in Software Generate barcode pdf417 in Software Special-Purpose Multithreaded Chip Multiprocessors




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8.3 Special-Purpose Multithreaded Chip Multiprocessors using software toencode pdf417 2d barcode for asp.net web,windows application Recommended GS1 barcodes for mobile apps wide (128 bytes) ports. T pdf417 2d barcode for None he narrow path is for direct load store communication with the SXU; the wide path is for instruction prefetch and DMA transactions with main memory, the PPE, and other SPEs. The on-chip interconnect between the PPE, the eight SPEs, the memory controller, and the I/O interfaces is called the element interconnect bus (EIB).

This is something of a misnomer in that the EIB is made up of four circular rings, two in each direction. Each ring can cater to three transactions simultaneously if they are spaced appropriately. The EIB is clocked at half the processor speed.

Each ring transaction carries 16 bytes of data. So, in theory, the bandwidth on the EIB is 16 4 3/2 = 96 bytes per processor cycle. In practice, this bandwidth will not be attained, because of con icting transactions or because the memory controller and I/O interfaces cannot sustain that rate.

Note that each unit, (i.e., each of the 12 elements connected to the EIB), is at a maximum distance of 6 from any other.

The EIB can be seen as a compromise between a bus and a full crossbar. Before leaving the description of the Cell processor, we want to emphasize the challenges faced by the user or the compiler to exploit such an architecture and thus the reasons why we consider it to be special-purpose. r Applications must be decomposed into threads, with the additional constraint that some threads might be better suited for the PPE and others (hopefully more) for the SPEs.

r SIMD parallelization must be detected for the SPEs and to a lesser extent for the PPE. This is not a simple task, as evidenced by the dif culties encountered by compiler writers who want to use MMX-like instructions ef ciently. r Not only SIMD but also code for short vectors has to be generated for the SPEs, with special attention to making scalar processing ef cient.

r Because the SPEs have no cache, all coherency requirements between the local memories of the SPEs have to be programmed in the application. In other words, all data allocation and all data transfers have to be part of the source code. r Because there is no hardware prefetching or cache purging, all commands for streaming data from and to memory have to be programmed for the memory interfaces.

r Because the pipelines of the PPE and the SPEs are long and their branch predictors are rather modest, special attention must be given to compiler-assisted branch prediction and predication. Granted, some of these challenges for example, vectorization and messagepassing primitives have been studied for a long time in the context of highperformance computing. Nonetheless, the overall magnitude of the dif culties is such that, though the Cell can be programmed ef ciently for the applications it was primarily intended for (namely, games and multimedia), it is less certain that more general-purpose scienti c applications can be run effectively.

. Multithreading and (Chip) Multiprocessing 8.3.2 A Network Processor PDF 417 for None : The Intel IXP 2800 Wide-area networks, such as the Internet, require processing units within the network to handle the ow of traf c.

At the onset of networking, these units were routers whose sole role was to forward packets in a hop-to-hop fashion from their origin to their destination. The functionality required of routers was minimal, and their implementation in the form of application-speci c integrated circuit (ASIC) components was the norm. However, with the exponential growth in network size, in transmission speed, and in networking applications more exibility became a necessity.

While retaining the use of fast ASICs on one hand and dedicating generalpurpose processors on the other hand had their advocates for some time, it is now recognized that programmable processors with ISAs and organizations more attuned to networking tasks are preferable. These processors are known as network processors (NPs). The workloads of network processors are quite varied and depend also on whether the NP is at the core or at the edge of the network.

Two fundamental tasks are IP forwarding at the core and packet classi cation at the edge. These two tasks involve looking at the header of the packet. IP forwarding, which as its name implies guides the packet to its destination, consists of a longest pre x match of a destination address contained in the header with a set of addresses contained in very large routing tables.

Packet classi cation is a re nement of IP forwarding where matching is performed on several elds of the header according to rules stored in relatively small access control lists. The matching rule with highest priority indicates the action to be performed on the packet, e.g.

, forward or discard. Among other tasks involving the header we can mention ow management for avoiding congestion in the network and statistics gathering for billing purposes. Encryption and authentication are tasks that require processing the data payload.

To understand the motivations behind the design of network processors, it is worth noting several characteristics of the workload: r In the great majority of cases, packets can be processed independently of each other. Therefore, NPs should have multiple processing units. For example, Cisco s Silicon Packet Processor has 188 cores, where evidently each core is much less than a full- edged processor.

r The data structures needed for many NP applications are large, and there is far from enough storage on chip to accommodate them. Therefore, access to external DRAMs should be optimized. To that effect, and because processing several packets in parallel is possible, coarse-grained multithreading with the possibility of process switching on DRAM accesses is a good option.

The Intel IXP 2800 that we present in more detail below has 16 cores, called microengines, which can each support eight hardware threads. r Access to the data structures has little or no locality. The tendency in NPs is to use local data memories rather than caches, although some research studies have shown that restricted caching schemes could be bene cial.

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