Compiler-based static vectorization is used widely to extract data-level parallelism from computation-intensive applications. Static vectorization is very effective in vectorizing traditional array-based applications. However, compilers' inability to do accurate interprocedural pointer disambiguation and interprocedural array dependence analysis severely limits vectorization opportunities. HW/SW codesigned processors provide an excellent opportunity to optimize the applications at runtime. The availability of dynamic application behavior at runtime helps in capturing vectorization opportunities generally missed by the compilers. This article proposes to complement the static vectorization with a speculative dynamic vectorizer in an HW/SW co...
Vectorization support in hardware continues to expand and grow as we still continue on superscalar a...
Data-level parallelism is frequently ignored or underutilized. Achieved through vector/SIMD capabili...
The major specific contributions are: (1) We introduce a new compiler analysis to identify the memor...
Compiler-based static vectorization is used widely to extract data-level parallelism from computatio...
Traditional vector architectures have been shown to be very effective in executing regular codes in ...
Traditional vector architectures have shown to be very effective for regular codes where the compile...
International audienceUsing SIMD instructions is essential in modern processor architecture for high...
SIMD accelerators are ubiquitous in microprocessors from different computing domains. Their high com...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Vectorization support in hardware continues to expand and grow as well we still continue on supersca...
Several ILP limit studies indicate the presence of considerable ILP across dynamically far-apart ins...
Accelerating program performance via SIMD vector units is very common in modern processors, as evide...
Recent hardware trends with GPUs and the increasing vector lengths of SSE-like ISA extensions for mu...
Vectorization is key to performance on modern hardware. Almost all architectures include some form o...
While industry continues to develop SIMD vector ISAs by providing new instructions and wider data-pa...
Vectorization support in hardware continues to expand and grow as we still continue on superscalar a...
Data-level parallelism is frequently ignored or underutilized. Achieved through vector/SIMD capabili...
The major specific contributions are: (1) We introduce a new compiler analysis to identify the memor...
Compiler-based static vectorization is used widely to extract data-level parallelism from computatio...
Traditional vector architectures have been shown to be very effective in executing regular codes in ...
Traditional vector architectures have shown to be very effective for regular codes where the compile...
International audienceUsing SIMD instructions is essential in modern processor architecture for high...
SIMD accelerators are ubiquitous in microprocessors from different computing domains. Their high com...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Vectorization support in hardware continues to expand and grow as well we still continue on supersca...
Several ILP limit studies indicate the presence of considerable ILP across dynamically far-apart ins...
Accelerating program performance via SIMD vector units is very common in modern processors, as evide...
Recent hardware trends with GPUs and the increasing vector lengths of SSE-like ISA extensions for mu...
Vectorization is key to performance on modern hardware. Almost all architectures include some form o...
While industry continues to develop SIMD vector ISAs by providing new instructions and wider data-pa...
Vectorization support in hardware continues to expand and grow as we still continue on superscalar a...
Data-level parallelism is frequently ignored or underutilized. Achieved through vector/SIMD capabili...
The major specific contributions are: (1) We introduce a new compiler analysis to identify the memor...