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Stream Processor Architecture (Hardcover, 2001 ed.)
Loot Price: R2,923
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Stream Processor Architecture (Hardcover, 2001 ed.)
Series: The Springer International Series in Engineering and Computer Science, 644
Expected to ship within 10 - 15 working days
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Media processing applications, such as three-dimensional graphics,
video compression, and image processing, currently demand 10-100
billion operations per second of sustained computation.
Fortunately, hundreds of arithmetic units can easily fit on a
modestly sized 1cm2 chip in modern VLSI. The challenge is to
provide these arithmetic units with enough data to enable them to
meet the computation demands of media processing applications.
Conventional storage hierarchies, which frequently include caches,
are unable to bridge the data bandwidth gap between modern DRAM and
tens to hundreds of arithmetic units. A data bandwidth hierarchy,
however, can bridge this gap by scaling the provided bandwidth
across the levels of the storage hierarchy. The stream programming
model enables media processing applications to exploit a data
bandwidth hierarchy effectively. Media processing applications can
naturally be expressed as a sequence of computation kernels that
operate on data streams. This programming model exposes the
locality and concurrency inherent in these applications and enables
them to be mapped efficiently to the data bandwidth hierarchy.
Stream programs are able to utilize inexperience local data
bandwidth when possible and consume expensive global data bandwidth
only when necessary. Stream Processor Architecture presents the
architecture of the Imagine streaming media processor, which
delivers a peak performance of 20 billion floating-point operations
per second. Imagine efficiently supports 48 arithmetic units with a
three-tiered data bandwidth hierarchy. At the base of the
hierarchy, the streaming memory system employs memory access
scheduling to maximize the sustained bandwidth of external DRAM. At
the center of the hierarchy, the global stream register file
enables streams of data to be recirculated directly from one
computation kernel to the next without returning data to memory.
Finally, local distributed register files that directly feed the
arithmetic units enable temporary data to be stored locally so that
it does not need to consume costly global register bandwidth. The
bandwidth hierarchy enables Imagine to achieve up to 96%
of the performance of a stream processor with infinite bandwidth
from memory and the global register file.
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