Streaming and Dynamic Compilers for High Performance Embedded
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Streaming and Dynamic Compilers for High Performance Embedded
HPEC 2002. Imagine Performance (Dally et. al 2002). 7.4 us per 1,024-point floating point complex FFT. 6.9 GFLOPs. FFT. 1.5us per row of 320 16-bit pixels.
Streaming and Dynamic Compilers for High Performance Embedded Computing Peter Mattson, Jonathan Springer, Charles Garrett, Richard Lethin Reservoir Labs, Inc.
r e s e r voir a b s
HPEC 2002
Outline
•
Streaming Languages for HPEC / Polymorphic Computer Architectures (PCA). – – – –
•
Mapping challenges R-Stream™ compiler for StreamC and KernelC Streaming Language Design Choices Thoughts on Mapping
Dynamic Compilation – – – – –
PCA objectives that dynamic compilation helps meet Runtime Compilation Issues/Technologies Example of How Dynamic Compilation Helps with Component Selection Insertion of New Code into Running Systems Approaches for using Dynamic Compilation Reliably
(6 ALUs * 8 PES * 400 MHz = 19.2 GOPS (peak), 0.18um, 2.56cm^2,) r e s e r voir a b s
HPEC 2002
Compiler Mapping Challenges Resources Parallel functional units Parallel tiles Distributed memories Local bypass wires Inter-tile wires
Mapping Requirements Identify Parallelism Partition Program Select Operators Place data Layout data Place computation Schedule computation
Constraints Functional unit availability Distributed register files Small bounded memories Small or no queues Partial interconnect
Increasing the arithmetic/memory ratio while holding silicon area fixed simultaneously increases resources and tightens constraints. è Automatic compilation MUCH harder è Place some burden on programmer and invest in compilers è Introduce new languages to assist programmer r e s e r voir a b s
HPEC 2002
KernelC / StreamC Languages (Stanford: Mattson 2001) KernelC Example
StreamC Example
kernel SAXPY( istream x_s, istream y_s, ostream result_s, float a) { loop_stream(x_s) { float x, y, result; x_s >> x; y_s >> y; result = a * x + y; result_s
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