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What is explicit parallel instruction computing (EPIC)?
What is instruction-level parallelism (ILP)?
Is instruction-level parallel pro-cessing a viable approach to achieving higher performance?
How does parallelism speed up a RISC program?
Explicitly parallel instruction computing (EPIC) is a term coined in 1997 by the HP–Intel alliance to describe a computing paradigm that researchers had been investigating since the early 1980s. This paradigm is also called Independence architectures.
Instruction-level parallelism (ILP) is the parallel or simultaneous execution of a sequence of instructions in a computer program. More specifically ILP refers to the average number of instructions run per step of this parallel execution.
Feb 1, 2000 · The authors developed the Explicitly Parallel Instruction Computing (EPIC) style of architecture to enable higher levels of instruction-level parallelism without unacceptable hardware complexity.
The Explicitly Parallel Instruction Computing (EPIC) style of architecture is an evolution of VLIW that has also absorbed many superscalar concepts, albeit in a form adapted to EPIC. EPIC provides a phi-losophy of how to build ILP processors, along with a set of architectural features that support this philoso-phy.
Explicitly parallel instruction computing (EPIC) is a term coined in 1997 by the HP–Intel alliance [1] to describe a computing paradigm that researchers had been investigating since the early 1980s. [2] This paradigm is also called Independence architectures.
The term EPIC (Explicitly Parallel Instruction Computing) was coined to describe the design philosophy and architecture style envisioned by HP, and the specific jointly designed instruction set architecture was named IA-64. More recently, Intel has preferred to use IPF (Itanium Processor Family) as the name of the instruction set architecture.
The authors developed the Explicitly Parallel Instruction Computing (EPIC) style of architecture to enable higher levels of instruction-level parallelism without unacceptable hardware complexity.
