Seymour Cray introduced the concept of vector architecture in 1970 as an elegant interpretation of SIMD (Single Instruction Multiple Data). Vector architecture exploits data parallelism by performing the same operations on different pieces of data concurrently. This contrasts with dataflow architectures, which achieve concurrency by executing different operations in parallel in a data-driven manner, and thread parallelism, which uses different threads of control. Vector processors implement SIMD by executing the same instructions across multiple data elements concurrently.

1. VECTOR ARCHITECTURE
Elagant interpretation of SIMD is called vector
architecture—by SEYMOUR CRAY in 1970

2. DATA PARALLELISM
CONCURRENCY ARISES FROM PERFORMING THE SAME
OPERATIONS ON DIFFERENT PIECES OF DATA
SINGLE INSTRUCTION MULTIPLE DATA (SIMD)
E.G., DOT PRODUCT OF TWO VECTORS
CONTRAST WITH DATA FLOW
CONCURRENCY ARISES FROM EXECUTING DIFFERENT OPERATIONS
IN PARALLEL (IN A DATA DRIVEN MANNER)
CONTRAST WITH THREAD (“CONTROL”) PARALLELISM
CONCURRENCY ARISES FROM EXECUTING DIFFERENT THREADS OF
CONTROL IN PARALLEL
SIMD EXPLOITS INSTRUCTION-LEVEL PARALLELISM
MULTIPLE INSTRUCTIONS CONCURRENT: INSTRUCTIONS HAPPEN TO BE THE
SAME

3. INTRODUCTION:

4. TYPES OF ARRAY PROCESSORS
THERE ARE BASICALLY TWO TYPES OF
ARRAY PROCESSORS:
 Attached Array Processors
 SIMD Array Processors

5. ATTACHED ARRAY PROCESSORS

6. SIMD ARRAY PROCESSORS

7. COMPONENTS OF VECTOR PROCESSORS

8. MODERN MULTIPLE PIPELINE VECTOR
COMPUTER:

9. VMIPS INSTRUCTIONS

10. EXAMPLE SIMD CODE

11. SIMILARITIES AND DIFFERENCES BETWEEN
VECTOR ARCHITECTURES AND GPUS
• BOTH ARCHITECTURES ARE DESIGNED TO EXECUTE
DATA-LEVEL PARALLEL PROGRAMS.
• THE VMIPS REGISTER FILE HOLDS ENTIRE
VECTORS—
THAT IS, A CONTIGUOUS BLOCK OF 64 DOUBLES. IN
CONTRAST, A SINGLE VECTOR IN A GPU WOULD BE
DISTRIBUTED ACROSS THE REGISTERS OF ALL SIMD
LANES.
• THE CALCULATIONS ARE IMPLICIT IN VECTOR
ARCHITECTURE BUT THEY ARE EXPLICIT IN GPUS.
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12. VECTOR ARCHITECTURE
• VECTOR ARCHITECTURES ARE EASIER TO
UNDERSTAND
AND TO COMPILE TO THAN OTHER SIMD VARIATIONS,
• BUT THEY WERE CONSIDERED TOO EXPENSIVE FOR
MICROPROCESSORS UNTIL RECENTLY.
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13. THANK YOU