Delite: Language Virtualization for Heterogeneous Parallel Computing

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Outline• Why high performance DSLs?• Examples of high performance DSLs• Delite: reusable components for DSL compilers• Delite: optimizing for heterogeneous architectures• Performance results
Heterogeneous Parallel ProgrammingPthreadsOpenMPSunT2Only way to get highperformance andperformance/wattCUDAOpenCLVerilogVHDLMPIPGASNvidiaFermiAlteraFPGACrayJaguar
Page 1: Delite: A Framework for Implementin
Page 5: The Ideal Parallel Programming Lang
Page 9 and 10: Our Approach: Three Views• Little
Page 11 and 12: OptiMLOptiML: An Implicitly Paralle
Page 13 and 14: k-means Generated CodeScaladef appl
Page 15 and 16: OptiQL: TPCH-Q1// lineItems: Table[
Page 17 and 18: OptiGraph: PageRankImplicitly paral
Page 19 and 20: OptiMeshval Flux = Field[Vertex,Dou
Page 21 and 22: Building a Language is Difficult•
Page 23 and 24: Matrix Exampleimport Matrixtrait Te
Page 26 and 27: DSL Optimizations• Override IR no
Page 28 and 29: Multiview Delite IRDomain UserInter
Page 30 and 31: Delite Op Fusing• Fuse Parallel O
Page 32 and 33: Multiview Delite IRDomain UserInter
Page 34 and 35: Re-Usable DSL ComponentsDSL Delite
Page 36 and 37: Mapping to Heterogeneous HardwareZi
Page 38 and 39: Outline• Delite: optimizing for h
Page 40 and 41: Heterogeneous Code Generation• De
Page 42: DeliteOp Code Generation• For eve
Page 46 and 47: Data Structure Generation• Datast
Page 49 and 50: 1. Map Operationval vec2 = vec1 + 2
Page 51 and 52: 2. Reduce Operationval vec2 = vec1.
Page 53:
4. Fusing Primitive Operationsval v
Page 57 and 58:
Normalized Execution Time1.00.31.61
Page 59 and 60:
Normalized Execution TimeOptiGraph:
Page 61 and 62:
Summary• DSLs can be used for bot
Page 63 and 64:
Lifting Control Structures• Const
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Delite: Language Virtualization for Heterogeneous Parallel Computing

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