computer assembly language 24 mar

Research Opportunities

  • Research opportunities are available, but many links may be outdated.

  • Funding can fluctuate frequently, so keep an eye on emerging grants or projects.

Conference at LaGuardia

  • A notable conference will be held at LaGuardia with discussions about resolutions on current topics such as quantum computing.

Quantum Computing Applications

  • Quantum computing is increasingly being utilized such as in power departments for load balancing with inconsistent energy sources.

  • Examples of energy sources that require load balancing:

    • Solar energy: Availability can vary throughout the day.

    • Wind energy: Similar to solar, dependent on environmental conditions.

    • Nuclear and fossil fuels: More predictable energy sources.

Internship Opportunities

  • Internship information session scheduled for Thursday at 4 PM (Eastern Time).

  • Organizations offering internships include Apollo missions (Artmis, mythological counterpart of Apollo) and Global Foundries located in Upstate New York.

  • Internships typically cover room and board; open to all majors.

Attendance and Participation

  • Attendance is measured through connection time in the online platform and may vary:

    • Individuals could receive attendance percentages based on active connection time.

  • Actual attendance may be factored in discussions about grades when borderline cases arise (e.g. B to B+, A to A-).

Floating Point Numbers

  • Floating point is essential for representing real numbers beyond just integers.

  • Example conversion of decimal to binary:

    • 3.5 can be represented as 1.1 in binary since:

      • 3 is 1 + 2

      • 0.5 is represented as the binary fraction.

  • Memory allocation for floating-point numbers is divided between integer and fractional parts.

Binary Representation of Floating Points

  • Detailed representations involve converting numbers into binary and valuing the fractional part:

    • Example: 0.125 = 1/8 = 2^(-3) in binary.

    • When fitting into memory, zero-padding is necessary to maintain fixed sizes.

  • Different languages (like C++) support floating-point declaration such as:

    • float x = 3.125;

Challenges with Floating Point Representation

  • Limitations of 12 bits can significantly constrain maximum values that can be represented (e.g., largest 4,096 using 16 bits).

  • The IEEE standardization allows more complex manipulation but partitions memory for special values (like infinity or NaN).

Floating Point and Decimal Calculations

  • Floating-point arithmetic can yield small inaccuracies due to limited precision.

  • Significant bytes relate to hexadecimal conversion:

    • Example 3.4e30 in standard form is 3.4 x 10^30.

  • Questions about precision involve needing to ensure decimal alignments during calculations.

Errors in Calculations

  • Errors in floating-point arithmetic accumulate with repeated operations, known as error propagation.

  • Historical context where a minor error caused major ramifications (e.g., the Patriot missile incident).

Quiz and Assessments

  • Regular quizzes to assess understanding of concepts, potentially covering conversions between binary, decimal, and hexadecimal formats.

  • Emphasis on practice and preparation for upcoming evaluations in the course.

Notes on Programming with Floats

  • In programming, care must be taken when checking equality of floating-point numbers due to inherent inaccuracies.

  • Safer programming practice avoids direct comparison of floats and often involves thresholds for approximation instead of equality.

Summary

  • Attendance, quantum computing, floating point representations, and errors in calculations are critical topics discussed during lectures.