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Compiling Algorithms for Heterogeneous Systems (Hardcover)
Loot Price: R1,460
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Compiling Algorithms for Heterogeneous Systems (Hardcover)
Series: Synthesis Lectures on Computer Architecture
Expected to ship within 10 - 15 working days
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Most emerging applications in imaging and machine learning must
perform immense amounts of computation while holding to strict
limits on energy and power. To meet these goals, architects are
building increasingly specialized compute engines tailored for
these specific tasks. The resulting computer systems are
heterogeneous, containing multiple processing cores with wildly
different execution models. Unfortunately, the cost of producing
this specialized hardware-and the software to control it-is
astronomical. Moreover, the task of porting algorithms to these
heterogeneous machines typically requires that the algorithm be
partitioned across the machine and rewritten for each specific
architecture, which is time consuming and prone to error. Over the
last several years, the authors have approached this problem using
domain-specific languages (DSLs): high-level programming languages
customized for specific domains, such as database manipulation,
machine learning, or image processing. By giving up generality,
these languages are able to provide high-level abstractions to the
developer while producing high-performance output. The purpose of
this book is to spur the adoption and the creation of
domain-specific languages, especially for the task of creating
hardware designs. In the first chapter, a short historical journey
explains the forces driving computer architecture today. Chapter 2
describes the various methods for producing designs for
accelerators, outlining the push for more abstraction and the tools
that enable designers to work at a higher conceptual level. From
there, Chapter 3 provides a brief introduction to image processing
algorithms and hardware design patterns for implementing them.
Chapters 4 and 5 describe and compare Darkroom and Halide, two
domain-specific languages created for image processing that produce
high-performance designs for both FPGAs and CPUs from the same
source code, enabling rapid design cycles and quick porting of
algorithms. The final section describes how the DSL approach also
simplifies the problem of interfacing between application code and
the accelerator by generating the driver stack in addition to the
accelerator configuration. This book should serve as a useful
introduction to domain-specialized computing for computer
architecture students and as a primer on domain-specific languages
and image processing hardware for those with more experience in the
field.
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