How far short of a double solve refinement finishes, and where each format stops
At its defaults it draws how far short of a double solve refinement finishes, and where each format stops. A log-log plot of how far short of a double-precision solve iterative refinement finishes, against the condition number, for three low-precision formats. Each curve sits flat at one and then climbs steeply past a vertical mark showing that format's threshold.
precision-threshold is one function in lib/figures/mixed.js —
mixed precision — refinement, and the threshold at 1/u. Everything below came out of it during this build, at
arguments taken from the essays rather than invented for this page. A figure here is the
figure a reader meets in an essay, and if the generator changes, this page changes with it.
At its defaults
Drawn even though every essay passes arguments — which on this site is every essay, at 100% of placements since the standard pass. A default nothing exercises is a trap for the next essay to call this with none, and this is the page where a default that has drifted from the figures around it becomes visible.
A log-log plot of how far short of a double-precision solve iterative refinement finishes, against the condition number, for three low-precision formats. Each curve sits flat at one and then climbs steeply past a vertical mark showing that format's threshold.
n: 30
The arguments are the ones Buying the accuracy back passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
A log-log plot of how far short of a double-precision solve iterative refinement finishes, against the condition number, for three low-precision formats. Each curve sits flat at one and then climbs steeply past a vertical mark showing that format's threshold.
n: 24
The arguments are the ones Where the hardware went passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
A log-log plot of how far short of a double-precision solve iterative refinement finishes, against the condition number, for three low-precision formats. Each curve sits flat at one and then climbs steeply past a vertical mark showing that format's threshold.
n: 8
The arguments are the ones Where the hardware went passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
A log-log plot of how far short of a double-precision solve iterative refinement finishes, against the condition number, for three low-precision formats. Each curve sits flat at one and then climbs steeply past a vertical mark showing that format's threshold.
n: 12
The arguments are the ones Where the hardware went passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
A log-log plot of how far short of a double-precision solve iterative refinement finishes, against the condition number, for three low-precision formats. Each curve sits flat at one and then climbs steeply past a vertical mark showing that format's threshold.
n: 32
The arguments are the ones Where the hardware went passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
A log-log plot of how far short of a double-precision solve iterative refinement finishes, against the condition number, for three low-precision formats. Each curve sits flat at one and then climbs steeply past a vertical mark showing that format's threshold.
What it checked while drawing
Every figure above checked its own claims on the way to being drawn, and a claim that failed
would have stopped the picture rather than shipped a wrong one. Those checks used to leave
no trace at all: a passing one returned true and the only evidence the figure had
checked anything was that nothing crashed. The list below is what they actually said, collected
by running this generator with an observer installed — not a description of
what it is believed to check.
35 distinct claims across 6 sets of arguments, grouped below by shape — because most of them are one sentence with a different number in it, and how many separate times that sentence was put to the test is the informative part.
the constructed matrix has κ = 10 — checked 10 times
fp32 lands on the double answer below its threshold, at κ = 10 — checked 3 times
fp16 / tf32 lands on the double answer below its threshold, at κ = 10 — checked 2 times
and finishes hopelessly short of it above, at κ = 10¹⁰
and finishes hopelessly short of it above, at κ = 10⁴
and finishes hopelessly short of it above, at κ = 10⁵
and finishes hopelessly short of it above, at κ = 10⁶
and finishes hopelessly short of it above, at κ = 10⁷
and finishes hopelessly short of it above, at κ = 10⁸
and finishes hopelessly short of it above, at κ = 10⁹
bfloat16 has a region below its threshold in this sweep
bfloat16 has a region past its threshold in this sweep
bfloat16 lands on the double answer below its threshold, at κ = 10
fp16 / tf32 has a higher threshold than bfloat16
fp16 / tf32 has a region below its threshold in this sweep
fp16 / tf32 has a region past its threshold in this sweep
fp32 has a higher threshold than fp16 / tf32
fp32 has a region below its threshold in this sweep
fp32 has a region past its threshold in this sweep
fp32 lands on the double answer below its threshold, at κ = 10⁴
fp32 lands on the double answer below its threshold, at κ = 10⁵
LU is for square matrices
matmul shapes agree
Against the rule
It draws a decomposition and prints its residual. It calls
luFactor, refine,
and every figure above carries the badge — which residualcheck verifies by looking
for it in the emitted SVG rather than by finding the call that builds one. A badge that is
constructed and then left out of the body is the failure that check exists for.
Across the library: the rule bites on 217
of 397 generators —
199 print a residual and
18 are exempt with a published reason;
180 factorise nothing.
Read from lib/residual-rule.js, which is the same body the gate enforces from,
and the gate's last check fails the build if this page and it disagree about any generator.
Where it is called
Changing this generator changes every figure on this list. That is what makes the list worth publishing rather than keeping in a check script.
Buying the accuracy back
Factorise in single precision, then correct the answer using residuals computed in double, and the result is what a full double-precision solve would have given. Compute those residuals in single instead and the identical algorithm, at identical cost, recovers nothing.
The arithmetic underneathWhere the hardware went
bfloat16 carries eight mantissa bits, which puts its refinement threshold at a condition number of 256. That is not an exotic matrix. It is an ordinary one, and past it the method still improves the answer by a factor of four hundred while getting nowhere near a usable one.